Fostering synergy between cell biology and systems biology.

PubMed

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Quantum biology of the retina.

PubMed

Sia, Paul Ikgan; Luiten, André N; Stace, Thomas M; Wood, John Pm; Casson, Robert J

2014-08-01

The emerging field of quantum biology has led to a greater understanding of biological processes at the microscopic level. There is recent evidence to suggest that non-trivial quantum features such as entanglement, tunnelling and coherence have evolved in living systems. These quantum features are particularly evident in supersensitive light-harvesting systems such as in photosynthesis and photoreceptors. A biomimetic strategy utilizing biological quantum phenomena might allow new advances in the field of quantum engineering, particularly in quantum information systems. In addition, a better understanding of quantum biological features may lead to novel medical diagnostic and therapeutic developments. In the present review, we discuss the role of quantum physics in biological systems with an emphasis on the retina. © 2014 Royal Australian and New Zealand College of Ophthalmologists.

First Steps in Computational Systems Biology: A Practical Session in Metabolic Modeling and Simulation

ERIC Educational Resources Information Center

Reyes-Palomares, Armando; Sanchez-Jimenez, Francisca; Medina, Miguel Angel

2009-01-01

A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever…

Mathematical modeling of physiological systems: an essential tool for discovery.

PubMed

Glynn, Patric; Unudurthi, Sathya D; Hund, Thomas J

2014-08-28

Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?" Copyright © 2014 Elsevier Inc. All rights reserved.

Systems interface biology

PubMed Central

Doyle, Francis J; Stelling, Jörg

2006-01-01

The field of systems biology has attracted the attention of biologists, engineers, mathematicians, physicists, chemists and others in an endeavour to create systems-level understanding of complex biological networks. In particular, systems engineering methods are finding unique opportunities in characterizing the rich behaviour exhibited by biological systems. In the same manner, these new classes of biological problems are motivating novel developments in theoretical systems approaches. Hence, the interface between systems and biology is of mutual benefit to both disciplines. PMID:16971329

"Toward High School Biology": Helping Middle School Students Understand Chemical Reactions and Conservation of Mass in Nonliving and Living Systems

ERIC Educational Resources Information Center

Herrmann-Abell, Cari F.; Koppal, Mary; Roseman, Jo Ellen

2016-01-01

Modern biology has become increasingly molecular in nature, requiring students to understand basic chemical concepts. Studies show, however, that many students fail to grasp ideas about atom rearrangement and conservation during chemical reactions or the application of these ideas to biological systems. To help provide students with a better…

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Focus issue: series on computational and systems biology.

PubMed

Gough, Nancy R

2011-09-06

The application of computational biology and systems biology is yielding quantitative insight into cellular regulatory phenomena. For the month of September, Science Signaling highlights research featuring computational approaches to understanding cell signaling and investigation of signaling networks, a series of Teaching Resources from a course in systems biology, and various other articles and resources relevant to the application of computational biology and systems biology to the study of signal transduction.

Biomimetic modelling.

PubMed Central

Vincent, Julian F V

2003-01-01

Biomimetics is seen as a path from biology to engineering. The only path from engineering to biology in current use is the application of engineering concepts and models to biological systems. However, there is another pathway: the verification of biological mechanisms by manufacture, leading to an iterative process between biology and engineering in which the new understanding that the engineering implementation of a biological system can bring is fed back into biology, allowing a more complete and certain understanding and the possibility of further revelations for application in engineering. This is a pathway as yet unformalized, and one that offers the possibility that engineers can also be scientists. PMID:14561351

Understanding Biological Regulation Through Synthetic Biology.

PubMed

Bashor, Caleb J; Collins, James J

2018-05-20

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry-biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Systems Biology-an interdisciplinary approach.

PubMed

Friboulet, Alain; Thomas, Daniel

2005-06-15

System-level approaches in biology are not new but foundations of "Systems Biology" are achieved only now at the beginning of the 21st century [Kitano, H., 2001. Foundations of Systems Biology. MIT Press, Cambridge, MA]. The renewed interest for a system-level approach is linked to the progress in collecting experimental data and to the limits of the "reductionist" approach. System-level understanding of native biological and pathological systems is needed to provide potential therapeutic targets. Examples of interdisciplinary approach in Systems Biology are described in U.S., Japan and Europe. Robustness in biology, metabolic engineering and idiotypic networks are discussed in the framework of Systems Biology.

Bioinspired Infrared Sensing Materials and Systems.

PubMed

Shen, Qingchen; Luo, Zhen; Ma, Shuai; Tao, Peng; Song, Chengyi; Wu, Jianbo; Shang, Wen; Deng, Tao

2018-05-11

Bioinspired engineering offers a promising alternative approach in accelerating the development of many man-made systems. Next-generation infrared (IR) sensing systems can also benefit from such nature-inspired approach. The inherent compact and uncooled operation of biological IR sensing systems provides ample inspiration for the engineering of portable and high-performance artificial IR sensing systems. This review overviews the current understanding of the biological IR sensing systems, most of which are thermal-based IR sensors that rely on either bolometer-like or photomechanic sensing mechanism. The existing efforts inspired by the biological IR sensing systems and possible future bioinspired approaches in the development of new IR sensing systems are also discussed in the review. Besides these biological IR sensing systems, other biological systems that do not have IR sensing capabilities but can help advance the development of engineered IR sensing systems are also discussed, and the related engineering efforts are overviewed as well. Further efforts in understanding the biological IR sensing systems, the learning from the integration of multifunction in biological systems, and the reduction of barriers to maximize the multidiscipline collaborations are needed to move this research field forward. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Collaborative Modelling of the Vascular System--Designing and Evaluating a New Learning Method for Secondary Students

ERIC Educational Resources Information Center

Haugwitz, Marion; Sandmann, Angela

2010-01-01

Understanding biological structures and functions is often difficult because of their complexity and micro-structure. For example, the vascular system is a complex and only partly visible system. Constructing models to better understand biological functions is seen as a suitable learning method. Models function as simplified versions of real…

Characterising the development of the understanding of human body systems in high-school biology students - a longitudinal study

NASA Astrophysics Data System (ADS)

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-10-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated using the Components Mechanisms Phenomena (CMP) framework for conceptual representation. We coded and analysed the repertory grid personal constructs of 67 high-school biology students at 4 points throughout the study. Our data analysis builds on the assumption that systems understanding entails a perception of all the system categories, including structures within the system (its Components), specific processes and interactions at the macro and micro levels (Mechanisms), and the Phenomena that present the macro scale of processes and patterns within a system. Our findings suggest that as the learning process progressed, the systems understanding of our students became more advanced, moving forward within each of the major CMP categories. Moreover, there was an increase in the mechanism complexity presented by the students, manifested by more students describing mechanisms at the molecular level. Thus, the 'mechanism' category and the micro level are critical components that enable students to understand system-level phenomena such as homeostasis.

Tracing organizing principles: learning from the history of systems biology.

PubMed

Green, Sara; Wolkenhauer, Olaf

2013-01-01

With the emergence of systems biology, the identification of organizing principles is being highlighted as a key research aim. Researchers attempt to "reverse engineer" the functional organization of biological systems using methodologies from mathematics, engineering and computer science while taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-twentieth century. The aim of this paper is to draw on this historical background in order to increase the understanding of the motivation behind the search for general principles and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational and system-level properties, ii) the inherent critique of reductionism and fragmentation of knowledge resulting from overspecialization, and iii) the insight that the ideal of formulating abstract organizing principles is complementary to, rather than conflicting with, the aim of formulating detailed explanations of biological mechanisms. We argue that looking back not only helps us understand the current practice but also points to possible future directions for systems biology.

Synthetic biology: insights into biological computation.

PubMed

Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

2016-04-18

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

A framework for evolutionary systems biology

PubMed Central

Loewe, Laurence

2009-01-01

Background Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Results Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. Conclusion EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications. PMID:19239699

No question about exciting questions in cell biology.

PubMed

Pollard, Thomas D

2013-12-01

Although we have a good grasp of many important processes in cell biology, including knowledge of many molecules involved and how they interact with each other, we still do not understand most of the dynamical features that are the essence of living systems. Fortunately, we now have the ability to dissect biological systems in enough detail to understand their dynamics, including the use of mathematical models to account for past observations and predict future experiments. This deep level of mechanistic understanding should be our goal—not simply to satisfy our scientific curiosity, but also to understand the causes of disease well enough to predict risks, make early diagnoses, and treat effectively. Many big questions remain to be answered before we reach this goal of understanding cellular dynamics.

Systematic analysis of signaling pathways using an integrative environment.

PubMed

Visvanathan, Mahesh; Breit, Marc; Pfeifer, Bernhard; Baumgartner, Christian; Modre-Osprian, Robert; Tilg, Bernhard

2007-01-01

Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

Future Science Teachers' Understandings of Diffusion and Osmosis Concepts

ERIC Educational Resources Information Center

Tomazic, Iztok; Vidic, Tatjana

2012-01-01

The concepts of diffusion and osmosis cross the disciplinary boundaries of physics, chemistry and biology. They are important for understanding how biological systems function. Since future (pre-service) science teachers in Slovenia encounter both concepts at physics, chemistry and biology courses during their studies, we assessed the first-,…

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

Systems cell biology

PubMed Central

Mast, Fred D.; Ratushny, Alexander V.

2014-01-01

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. PMID:25225336

Dissecting innate immune responses with the tools of systems biology.

PubMed

Smith, Kelly D; Bolouri, Hamid

2005-02-01

Systems biology strives to derive accurate predictive descriptions of complex systems such as innate immunity. The innate immune system is essential for host defense, yet the resulting inflammatory response must be tightly regulated. Current understanding indicates that this system is controlled by complex regulatory networks, which maintain homoeostasis while accurately distinguishing pathogenic infections from harmless exposures. Recent studies have used high throughput technologies and computational techniques that presage predictive models and will be the foundation of a systems level understanding of innate immunity.

Pushing the lipid envelope: using bio-inspired nanocomposites to understand and exploit lipid membrane limitations

NASA Astrophysics Data System (ADS)

Montano, Gabriel

Lipids serve as the organizing matrix material for biological membranes, the site of interaction of cells with the external environment. . As such, lipids play a critical role in structure/function relationships of an extraordinary number of critical biological processes. In this talk, we will look at bio-inspired membrane assemblies to better understand the roles of lipids in biological systems as well as attempt to generate materials that can mimic and potentially advance upon biological membrane processes. First, we will investigate the response of lipids to adverse conditions. In particular, I will present data that demonstrates the response of lipids to harsh conditions and how such responses can be exploited to generate nanocomposite rearrangements. I will also show the effect of adding the endotoxin lipopolysaccharide (LPS) to lipid bilayer assemblies and describe implications on our understanding of LPS organization in biological systems as well as describe induced lipid modifications that can be exploited to organize membrane composites with precise, two-dimensional geometric control. Lastly, I will describe the use of amphiphilic block copolymers to create membrane nanocomposites capable of mimicking biological systems. In particular, I will describe the use of our polymer-based membranes in creating artificial photosynthetic assemblies that rival biological systems in function in a more flexible, dynamic matrix.

Cross-hierarchy systems principles.

PubMed

Goentoro, Lea

2017-02-01

One driving motivation of systems biology is the search for general principles that govern the design of biological systems. But questions often arise as to what kind of general principles biology could have. Concepts from engineering such as robustness and modularity are indeed becoming a regular way of describing biological systems. Another source of potential general principles is the emerging similarities found in processes across biological hierarchies. In this piece, I describe several emerging cross-hierarchy similarities. Identification of more cross-hierarchy principles, and understanding the implications these convergence have on the construction of biological systems, I believe, present exciting challenges for systems biology in the decades to come.

Half dozen of one, six billion of the other: What can small- and large-scale molecular systems biology learn from one another?

PubMed

Mellis, Ian A; Raj, Arjun

2015-10-01

Small-scale molecular systems biology, by which we mean the understanding of a how a few parts work together to control a particular biological process, is predicated on the assumption that cellular regulation is arranged in a circuit-like structure. Results from the omics revolution have upset this vision to varying degrees by revealing a high degree of interconnectivity, making it difficult to develop a simple, circuit-like understanding of regulatory processes. We here outline the limitations of the small-scale systems biology approach with examples from research into genetic algorithms, genetics, transcriptional network analysis, and genomics. We also discuss the difficulties associated with deriving true understanding from the analysis of large data sets and propose that the development of new, intelligent, computational tools may point to a way forward. Throughout, we intentionally oversimplify and talk about things in which we have little expertise, and it is likely that many of our arguments are wrong on one level or another. We do believe, however, that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach, and our goal is to provoke thought along these lines. © 2015 Mellis and Raj; Published by Cold Spring Harbor Laboratory Press.

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Search for organising principles: understanding in systems biology.

PubMed

Mesarovic, M D; Sreenath, S N; Keene, J D

2004-06-01

Due in large measure to the explosive progress in molecular biology, biology has become arguably the most exciting scientific field. The first half of the 21st century is sometimes referred to as the 'era of biology', analogous to the first half of the 20th century, which was considered to be the 'era of physics'. Yet, biology is facing a crisis--or is it an opportunity--reminiscent of the state of biology in pre-double-helix time. The principal challenge facing systems biology is complexity. According to Hood, 'Systems biology defines and analyses the interrelationships of all of the elements in a functioning system in order to understand how the system works.' With 30000+ genes in the human genome the study of all relationships simultaneously becomes a formidably complex problem. Hanahan and Weinberg raised the question as to whether progress will consist of 'adding further layers of complexity to a scientific literature that is already complex almost beyond measure' or whether the progress will lead to a 'science with a conceptual structure and logical coherence that rivals that of chemistry or physics.' At the core of the challenge is the need for a new approach, a shift from reductionism to a holistic perspective. However, more than just a pronouncement of a new approach is needed. We suggest that what is needed is to provide a conceptual framework for systems biology research. We propose that the concept of a complex system, i.e. a system of systems as defined in mathematical general systems theory (MGST), is central to provide such a framework. We further argue that for a deeper understanding in systems biology investigations should go beyond building numerical mathematical or computer models--important as they are. Biological phenomena cannot be predicted with the level of numerical precision as in classical physics. Explanations in terms of how the categories of systems are organised to function in ever changing conditions are more revealing. Non-numerical mathematical tools are appropriate for the task. Such a categorical perspective led us to propose that the core of understanding in systems biology depends on the search for organising principles rather than solely on construction of predictive descriptions (i.e. models) that exactly outline the evolution of systems in space and time. The search for organising principles requires an identification/discovery of new concepts and hypotheses. Some of them, such as coordination motifs for transcriptional regulatory networks and bounded autonomy of levccels in a hierarchy, are outlined in this article. Experimental designs are outlined to help verify the applicability of the interaction balance principle of coordination to transcriptional and posttranscriptional networks.

Systems cell biology.

PubMed

Mast, Fred D; Ratushny, Alexander V; Aitchison, John D

2014-09-15

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. © 2014 Mast et al.

Microgravity Fluids for Biology, Workshop

NASA Technical Reports Server (NTRS)

Griffin, DeVon; Kohl, Fred; Massa, Gioia D.; Motil, Brian; Parsons-Wingerter, Patricia; Quincy, Charles; Sato, Kevin; Singh, Bhim; Smith, Jeffrey D.; Wheeler, Raymond M.

2013-01-01

Microgravity Fluids for Biology represents an intersection of biology and fluid physics that present exciting research challenges to the Space Life and Physical Sciences Division. Solving and managing the transport processes and fluid mechanics in physiological and biological systems and processes are essential for future space exploration and colonization of space by humans. Adequate understanding of the underlying fluid physics and transport mechanisms will provide new, necessary insights and technologies for analyzing and designing biological systems critical to NASAs mission. To enable this mission, the fluid physics discipline needs to work to enhance the understanding of the influence of gravity on the scales and types of fluids (i.e., non-Newtonian) important to biology and life sciences. In turn, biomimetic, bio-inspired and synthetic biology applications based on physiology and biology can enrich the fluid mechanics and transport phenomena capabilities of the microgravity fluid physics community.

Understanding the immune response to seasonal influenza vaccination in older adults: a systems biology approach.

PubMed

Lambert, Nathaniel D; Ovsyannikova, Inna G; Pankratz, V Shane; Jacobson, Robert M; Poland, Gregory A

2012-08-01

Annual vaccination against seasonal influenza is recommended to decrease disease-related mortality and morbidity. However, one population that responds suboptimally to influenza vaccine is adults over the age of 65 years. The natural aging process is associated with a complex deterioration of multiple components of the host immune system. Research into this phenomenon, known as immunosenescence, has shown that aging alters both the innate and adaptive branches of the immune system. The intricate mechanisms involved in immune response to influenza vaccine, and how these responses are altered with age, have led us to adopt a more encompassing systems biology approach to understand exactly why the response to vaccination diminishes with age. Here, the authors review what changes occur with immunosenescence, and some immunogenetic factors that influence response, and outline the systems biology approach to understand the immune response to seasonal influenza vaccination in older adults.

Applications of systems approaches in the study of rheumatic diseases.

PubMed

Kim, Ki-Jo; Lee, Saseong; Kim, Wan-Uk

2015-03-01

The complex interaction of molecules within a biological system constitutes a functional module. These modules are then acted upon by both internal and external factors, such as genetic and environmental stresses, which under certain conditions can manifest as complex disease phenotypes. Recent advances in high-throughput biological analyses, in combination with improved computational methods for data enrichment, functional annotation, and network visualization, have enabled a much deeper understanding of the mechanisms underlying important biological processes by identifying functional modules that are temporally and spatially perturbed in the context of disease development. Systems biology approaches such as these have produced compelling observations that would be impossible to replicate using classical methodologies, with greater insights expected as both the technology and methods improve in the coming years. Here, we examine the use of systems biology and network analysis in the study of a wide range of rheumatic diseases to better understand the underlying molecular and clinical features.

Integrative systems and synthetic biology of cell-matrix adhesion sites.

PubMed

Zamir, Eli

2016-09-02

The complexity of cell-matrix adhesion convolves its roles in the development and functioning of multicellular organisms and their evolutionary tinkering. Cell-matrix adhesion is mediated by sites along the plasma membrane that anchor the actin cytoskeleton to the matrix via a large number of proteins, collectively called the integrin adhesome. Fundamental challenges for understanding how cell-matrix adhesion sites assemble and function arise from their multi-functionality, rapid dynamics, large number of components and molecular diversity. Systems biology faces these challenges in its strive to understand how the integrin adhesome gives rise to functional adhesion sites. Synthetic biology enables engineering intracellular modules and circuits with properties of interest. In this review I discuss some of the fundamental questions in systems biology of cell-matrix adhesion and how synthetic biology can help addressing them.

Systems biology approaches to understand the effects of nutrition and promote health.

PubMed

Badimon, Lina; Vilahur, Gemma; Padro, Teresa

2017-01-01

Within the last years the implementation of systems biology in nutritional research has emerged as a powerful tool to understand the mechanisms by which dietary components promote health and prevent disease as well as to identify the biologically active molecules involved in such effects. Systems biology, by combining several '-omics' disciplines (mainly genomics/transcriptomics, proteomics and metabolomics), creates large data sets that upon computational integration provide in silico predictive networks that allow a more extensive analysis of the individual response to a nutritional intervention and provide a more global comprehensive understanding of how diet may influence health and disease. Numerous studies have demonstrated that diet and particularly bioactive food components play a pivotal role in helping to counteract environmental-related oxidative damage. Oxidative stress is considered to be strongly implicated in ageing and the pathophysiology of numerous diseases including neurodegenerative disease, cancers, metabolic disorders and cardiovascular diseases. In the following review we will provide insights into the role of systems biology in nutritional research and focus on transcriptomic, proteomic and metabolomics studies that have demonstrated the ability of functional foods and their bioactive components to fight against oxidative damage and contribute to health benefits. © 2016 The British Pharmacological Society.

How does undergraduate college biology students' level of understanding, in regard to the role of the seed plant root system, relate to their level of understanding of photosynthesis?

NASA Astrophysics Data System (ADS)

Njeng'ere, James Gicheha

This research study investigated how undergraduate college biology students' level of understanding of the role of the seed plant root system relates to their level of understanding of photosynthesis. This research was conducted with 65 undergraduate non-majors biology who had completed 1 year of biology at Louisiana State University in Baton Rouge and Southeastern Louisiana University in Hammond. A root probe instrument was developed from some scientifically acceptable propositional statements about the root system, the process of photosynthesis, as well as the holistic nature of the tree. These were derived from research reviews of the science education and the arboriculture literature. This was administered to 65 students selected randomly from class lists of the two institutions. Most of the root probe's items were based on the Live Oak tree. An in-depth, clinical interview-based analysis was conducted with 12 of those tested students. A team of root experts participated by designing, validating and answering the same questions that the students were asked. A "systems" lens as defined by a team of college instructors, root experts (Shigo, 1991), and this researcher was used to interpret the results. A correlational coefficient determining students' level of understanding of the root system and their level of understanding of the process of photosynthesis was established by means of Pearson's r correlation (r = 0.328) using the SAS statistical analysis (SAS, 1987). From this a coefficient of determination (r2 = 0.104) was determined. Students' level of understanding of the Live Oak root system (mean score 5.94) was not statistically different from their level of understanding of the process of photosynthesis (mean score 5.54) as assessed by the root probe, t (129) = 0.137, p > 0.05 one tailed-test. This suggests that, to some degree, level of the root system limits level of understanding of photosynthesis and vice versa. Analysis of quantitative and qualitative data revealed that students who applied principles of systems thinking performed better than those who did not. Students' understanding of the root system of the Live Oak tree was hindered by understanding of, plant food, the nonwoody roots, and the tree as a system.

From noise to synthetic nucleoli: can synthetic biology achieve new insights?

PubMed

Ciechonska, Marta; Grob, Alice; Isalan, Mark

2016-04-18

Synthetic biology aims to re-organise and control biological components to make functional devices. Along the way, the iterative process of designing and testing gene circuits has the potential to yield many insights into the functioning of the underlying chassis of cells. Thus, synthetic biology is converging with disciplines such as systems biology and even classical cell biology, to give a new level of predictability to gene expression, cell metabolism and cellular signalling networks. This review gives an overview of the contributions that synthetic biology has made in understanding gene expression, in terms of cell heterogeneity (noise), the coupling of growth and energy usage to expression, and spatiotemporal considerations. We mainly compare progress in bacterial and mammalian systems, which have some of the most-developed engineering frameworks. Overall, one view of synthetic biology can be neatly summarised as "creating in order to understand."

On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

PubMed

Gomez-Ramirez, Jaime; Sanz, Ricardo

2013-09-01

One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.

Toward an integrated software platform for systems pharmacology

PubMed Central

Ghosh, Samik; Matsuoka, Yukiko; Asai, Yoshiyuki; Hsin, Kun-Yi; Kitano, Hiroaki

2013-01-01

Understanding complex biological systems requires the extensive support of computational tools. This is particularly true for systems pharmacology, which aims to understand the action of drugs and their interactions in a systems context. Computational models play an important role as they can be viewed as an explicit representation of biological hypotheses to be tested. A series of software and data resources are used for model development, verification and exploration of the possible behaviors of biological systems using the model that may not be possible or not cost effective by experiments. Software platforms play a dominant role in creativity and productivity support and have transformed many industries, techniques that can be applied to biology as well. Establishing an integrated software platform will be the next important step in the field. © 2013 The Authors. Biopharmaceutics & Drug Disposition published by John Wiley & Sons, Ltd. PMID:24150748

The pedestrian watchmaker: Genetic clocks from engineered oscillators

PubMed Central

Cookson, Natalie A.; Tsimring, Lev S.; Hasty, Jeff

2010-01-01

The crucial role of time-keeping has required organisms to develop sophisticated regulatory networks to ensure the reliable propagation of periodic behavior. These biological clocks have long been a focus of research; however, a clear understanding of how they maintain oscillations in the face of unpredictable environments and the inherent noise of biological systems remains elusive. Here, we review the current understanding of circadian oscillations using Drosophila melanogaster as a typical example and discuss the utility of an alternative synthetic biology approach to studying these highly intricate systems. PMID:19903483

A Framework for Understanding the Characteristics of Complexity in Biology

ERIC Educational Resources Information Center

Dauer, Joseph; Dauer, Jenny

2016-01-01

Understanding the functioning of natural systems is not easy, although there is general agreement that understanding complex systems is an important goal for science education. Defining what makes a natural system complex will assist in identifying gaps in research on student reasoning about systems. The goal of this commentary is to propose a…

Modeling systems-level dynamics: Understanding without mechanistic explanation in integrative systems biology.

PubMed

MacLeod, Miles; Nersessian, Nancy J

2015-02-01

In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding." Copyright © 2014 Elsevier Ltd. All rights reserved.

Thermostability of biological systems: fundamentals, challenges, and quantification.

PubMed

He, Xiaoming

2011-01-01

This review examines the fundamentals and challenges in engineering/understanding the thermostability of biological systems over a wide temperature range (from the cryogenic to hyperthermic regimen). Applications of the bio-thermostability engineering to either destroy unwanted or stabilize useful biologicals for the treatment of diseases in modern medicine are first introduced. Studies on the biological responses to cryogenic and hyperthermic temperatures for the various applications are reviewed to understand the mechanism of thermal (both cryo and hyperthermic) injury and its quantification at the molecular, cellular and tissue/organ levels. Methods for quantifying the thermophysical processes of the various applications are then summarized accounting for the effect of blood perfusion, metabolism, water transport across cell plasma membrane, and phase transition (both equilibrium and non-equilibrium such as ice formation and glass transition) of water. The review concludes with a summary of the status quo and future perspectives in engineering the thermostability of biological systems.

Thermostability of Biological Systems: Fundamentals, Challenges, and Quantification

PubMed Central

He, Xiaoming

2011-01-01

This review examines the fundamentals and challenges in engineering/understanding the thermostability of biological systems over a wide temperature range (from the cryogenic to hyperthermic regimen). Applications of the bio-thermostability engineering to either destroy unwanted or stabilize useful biologicals for the treatment of diseases in modern medicine are first introduced. Studies on the biological responses to cryogenic and hyperthermic temperatures for the various applications are reviewed to understand the mechanism of thermal (both cryo and hyperthermic) injury and its quantification at the molecular, cellular and tissue/organ levels. Methods for quantifying the thermophysical processes of the various applications are then summarized accounting for the effect of blood perfusion, metabolism, water transport across cell plasma membrane, and phase transition (both equilibrium and non-equilibrium such as ice formation and glass transition) of water. The review concludes with a summary of the status quo and future perspectives in engineering the thermostability of biological systems. PMID:21769301

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

PubMed

Rao, Rohit T; Scherholz, Megerle L; Hartmanshenn, Clara; Bae, Seul-A; Androulakis, Ioannis P

2017-12-05

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Designing and testing a classroom curriculum to teach preschoolers about the biology of physical activity: The respiration system as an underlying biological causal mechanism

NASA Astrophysics Data System (ADS)

Ewing, Tracy S.

The present study examined young children's understanding of respiration and oxygen as a source of vital energy underlying physical activity. Specifically, the purpose of the study was to explore whether a coherent biological theory, characterized by an understanding that bodily parts (heart and lungs) and processes (oxygen in respiration) as part of a biological system, can be taught as a foundational concept to reason about physical activity. The effects of a biology-based intervention curriculum designed to teach preschool children about bodily functions as a part of the respiratory system, the role of oxygen as a vital substance and how physical activity acts an energy source were examined. Participants were recruited from three private preschool classrooms (two treatment; 1 control) in Southern California and included a total of 48 four-year-old children (30 treatment; 18 control). Findings from this study suggested that young children could be taught relevant biological concepts about the role of oxygen in respiratory processes. Children who received biology-based intervention curriculum made significant gains in their understanding of the biology of respiration, identification of physical and sedentary activities. In addition these children demonstrated that coherence of conceptual knowledge was correlated with improved accuracy at activity identification and reasoning about the inner workings of the body contributing to endurance. Findings from this study provided evidence to support the benefits of providing age appropriate but complex coherent biological instruction to children in early childhood settings.

Analyzing Change in Students' Gene-to-Evolution Models in College-Level Introductory Biology

ERIC Educational Resources Information Center

Dauer, Joseph T.; Momsen, Jennifer L.; Speth, Elena Bray; Makohon-Moore, Sasha C.; Long, Tammy M.

2013-01-01

Research in contemporary biology has become increasingly complex and organized around understanding biological processes in the context of systems. To better reflect the ways of thinking required for learning about systems, we developed and implemented a pedagogical approach using box-and-arrow models (similar to concept maps) as a foundational…

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

PubMed Central

2011-01-01

Background Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context. Findings We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology. Conclusion FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga. PMID:22035155

Pattern dynamics of the reaction-diffusion immune system.

PubMed

Zheng, Qianqian; Shen, Jianwei; Wang, Zhijie

2018-01-01

In this paper, we will investigate the effect of diffusion, which is ubiquitous in nature, on the immune system using a reaction-diffusion model in order to understand the dynamical behavior of complex patterns and control the dynamics of different patterns. Through control theory and linear stability analysis of local equilibrium, we obtain the optimal condition under which the system loses stability and a Turing pattern occurs. By combining mathematical analysis and numerical simulation, we show the possible patterns and how these patterns evolve. In addition, we establish a bridge between the complex patterns and the biological mechanism using the results from a previous study in Nature Cell Biology. The results in this paper can help us better understand the biological significance of the immune system.

Using graph theory to analyze biological networks

PubMed Central

2011-01-01

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. PMID:21527005

The role of mechanics in biological and bio-inspired systems.

PubMed

Egan, Paul; Sinko, Robert; LeDuc, Philip R; Keten, Sinan

2015-07-06

Natural systems frequently exploit intricate multiscale and multiphasic structures to achieve functionalities beyond those of man-made systems. Although understanding the chemical make-up of these systems is essential, the passive and active mechanics within biological systems are crucial when considering the many natural systems that achieve advanced properties, such as high strength-to-weight ratios and stimuli-responsive adaptability. Discovering how and why biological systems attain these desirable mechanical functionalities often reveals principles that inform new synthetic designs based on biological systems. Such approaches have traditionally found success in medical applications, and are now informing breakthroughs in diverse frontiers of science and engineering.

Systems Biology Approach in Hypertension Research.

PubMed

Delles, Christian; Husi, Holger

2017-01-01

Systems biology is an approach to study all genes, gene transcripts, proteins, metabolites, and their interactions in specific cells, tissues, organs, or the whole organism. It is based on data derived from high-throughput analytical technologies and bioinformatics tools to analyze these data, and aims to understand the whole system rather than individual aspects of it. Systems biology can be applied to virtually all conditions and diseases and therefore also to hypertension and its underlying vascular disorders. Unlike other methods in this book there is no clear-cut protocol to explain a systems biology approach. We will instead outline some of the most important and common steps in the generation and analysis of systems biology data.

Biological organization of the extraocular muscles.

PubMed

Spencer, Robert F; Porter, John D

2006-01-01

Extraocular muscle is fundamentally distinct from other skeletal muscles. Here, we review the biological organization of the extraocular muscles with the intent of understanding this novel muscle group in the context of oculomotor system function. The specific objectives of this review are threefold. The first objective is to understand the anatomic arrangement of the extraocular muscles and their compartmental or layered organization in the context of a new concept of orbital mechanics, the active pulley hypothesis. The second objective is to present an integrated view of the morphologic, cellular, and molecular differences between extraocular and the more traditional skeletal muscles. The third objective is to relate recent data from functional and molecular biology studies to the established extraocular muscle fiber types. Developmental mechanisms that may be responsible for the divergence of the eye muscles from a skeletal muscle prototype also are considered. Taken together, a multidisciplinary understanding of extraocular muscle biology in health and disease provides insights into oculomotor system function and malfunction. Moreover, because the eye muscles are selectively involved or spared in a variety of neuromuscular diseases, knowledge of their biology may improve current pathogenic models of and treatments for devastating systemic diseases.

Networking Omic Data to Envisage Systems Biological Regulation.

PubMed

Kalapanulak, Saowalak; Saithong, Treenut; Thammarongtham, Chinae

To understand how biological processes work, it is necessary to explore the systematic regulation governing the behaviour of the processes. Not only driving the normal behavior of organisms, the systematic regulation evidently underlies the temporal responses to surrounding environments (dynamics) and long-term phenotypic adaptation (evolution). The systematic regulation is, in effect, formulated from the regulatory components which collaboratively work together as a network. In the drive to decipher such a code of lives, a spectrum of technologies has continuously been developed in the post-genomic era. With current advances, high-throughput sequencing technologies are tremendously powerful for facilitating genomics and systems biology studies in the attempt to understand system regulation inside the cells. The ability to explore relevant regulatory components which infer transcriptional and signaling regulation, driving core cellular processes, is thus enhanced. This chapter reviews high-throughput sequencing technologies, including second and third generation sequencing technologies, which support the investigation of genomics and transcriptomics data. Utilization of this high-throughput data to form the virtual network of systems regulation is explained, particularly transcriptional regulatory networks. Analysis of the resulting regulatory networks could lead to an understanding of cellular systems regulation at the mechanistic and dynamics levels. The great contribution of the biological networking approach to envisage systems regulation is finally demonstrated by a broad range of examples.

Joining Forces: The Chemical Biology-Medicinal Chemistry Continuum.

PubMed

Plowright, Alleyn T; Ottmann, Christian; Arkin, Michelle; Auberson, Yves P; Timmerman, Henk; Waldmann, Herbert

2017-09-21

The scientific advances being made across all disciplines are creating ever-increasing opportunities to enhance our knowledge of biological systems and how they relate to human disease. One of the central driving forces in discovering new medicines is medicinal chemistry, where the design and synthesis of novel compounds has led to multiple drugs. Chemical biology, sitting at the interface of many disciplines, has now emerged as a major contributor to the understanding of biological systems and is becoming an integral part of drug discovery. Bringing chemistry and biology much closer and blurring the boundaries between disciplines is creating new opportunities to probe and understand biology; both disciplines play key roles and need to join forces and work together effectively to synergize their impact. The power of chemical biology will then reach its full potential and drive innovation, leading to the discovery of transformative medicines to treat patients. Advances in cancer biology and drug discovery highlight this potential. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biological diversity, ecological integrity, and neotropical migrants: New perspectives for wildlife management

Treesearch

Brian A. Maurer

1993-01-01

New initiatives in wildlife management have come from the realization that birds can be used as indicators of ecosystem health. Conceptually, biological diversity includes processes working at all scales in biological hierarchies that compose the natural world. Recent advances in the understanding of ecological systems suggest they are nonequilibrium systems, and must...

Integrative Systems Biology for Data Driven Knowledge Discovery

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2015-01-01

Integrative systems biology is an approach that brings together diverse high throughput experiments and databases to gain new insights into biological processes or systems at molecular through physiological levels. These approaches rely on diverse high-throughput experimental techniques that generate heterogeneous data by assaying varying aspects of complex biological processes. Computational approaches are necessary to provide an integrative view of these experimental results and enable data-driven knowledge discovery. Hypotheses generated from these approaches can direct definitive molecular experiments in a cost effective manner. Using integrative systems biology approaches, we can leverage existing biological knowledge and large-scale data to improve our understanding of yet unknown components of a system of interest and how its malfunction leads to disease. PMID:21044756

The value of mechanistic biophysical information for systems-level understanding of complex biological processes such as cytokinesis.

PubMed

Pollard, Thomas D

2014-12-02

This review illustrates the value of quantitative information including concentrations, kinetic constants and equilibrium constants in modeling and simulating complex biological processes. Although much has been learned about some biological systems without these parameter values, they greatly strengthen mechanistic accounts of dynamical systems. The analysis of muscle contraction is a classic example of the value of combining an inventory of the molecules, atomic structures of the molecules, kinetic constants for the reactions, reconstitutions with purified proteins and theoretical modeling to account for the contraction of whole muscles. A similar strategy is now being used to understand the mechanism of cytokinesis using fission yeast as a favorable model system. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Systems biology for understanding and engineering of heterotrophic oleaginous microorganisms.

PubMed

Park, Beom Gi; Kim, Minsuk; Kim, Joonwon; Yoo, Heewang; Kim, Byung-Gee

2017-01-01

Heterotrophic oleaginous microorganisms continue to draw interest as they can accumulate a large amount of lipids which is a promising feedstock for the production of biofuels and oleochemicals. Nutrient limitation, especially nitrogen limitation, is known to effectively trigger the lipid production in these microorganisms. For the aim of developing improved strains, the mechanisms behind the lipid production have been studied for a long time. Nowadays, system-level understanding of their metabolism and associated metabolic switches is attainable with modern systems biology tools. This work reviews the systems biology studies, based on (i) top-down, large-scale 'omics' tools, and (ii) bottom-up, mathematical modeling methods, on the heterotrophic oleaginous microorganisms with an emphasis on further application to metabolic engineering. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Revealing evolutionary pathways by fitness landscape reconstruction.

PubMed

Kogenaru, Manjunatha; de Vos, Marjon G J; Tans, Sander J

2009-01-01

The concept of epistasis has since long been used to denote non-additive fitness effects of genetic changes and has played a central role in understanding the evolution of biological systems. Owing to an array of novel experimental methodologies, it has become possible to experimentally determine epistatic interactions as well as more elaborate genotype-fitness maps. These data have opened up the investigation of a host of long-standing questions in evolutionary biology, such as the ruggedness of fitness landscapes and the accessibility of mutational trajectories, the evolution of sex, and the origin of robustness and modularity. Here we review this recent and timely marriage between systems biology and evolutionary biology, which holds the promise to understand evolutionary dynamics in a more mechanistic and predictive manner.

Applications of systems biology towards microbial fuel production.

PubMed

Gowen, Christopher M; Fong, Stephen S

2011-10-01

Harnessing the immense natural diversity of biological functions for economical production of fuel has enormous potential benefits. Inevitably, however, the native capabilities for any given organism must be modified to increase the productivity or efficiency of a biofuel bioprocess. From a broad perspective, the challenge is to sufficiently understand the details of cellular functionality to be able to prospectively predict and modify the cellular function of a microorganism. Recent advances in experimental and computational systems biology approaches can be used to better understand cellular level function and guide future experiments. With pressure to quickly develop viable, renewable biofuel processes a balance must be maintained between obtaining depth of biological knowledge and applying that knowledge. Copyright © 2011 Elsevier Ltd. All rights reserved.

Understanding Digital Learning from the Perspective of Systems Dynamics

ERIC Educational Resources Information Center

Kok, Ayse

2009-01-01

The System Dynamics approach can be seen as a new way of understanding dynamical phenonema (natural, physical, biological, etc.) that occur in our daily lives taking into consideration not only single pairs of cause-effect variables, but the functioning of the system as a whole. This approach also provides the students with a new understanding in…

Synergism of Nanomaterials with Physical Stimuli for Biology and Medicine.

PubMed

Shin, Tae-Hyun; Cheon, Jinwoo

2017-03-21

Developing innovative tools that facilitate the understanding of sophisticated biological systems has been one of the Holy Grails in the physical and biological sciences. In this Commentary, we discuss recent advances, opportunities, and challenges in the use of nanomaterials as a precision tool for biology and medicine.

Micro-separation toward systems biology.

PubMed

Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

2006-02-17

Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

Systems biology and mechanics of growth.

PubMed

Eskandari, Mona; Kuhl, Ellen

2015-01-01

In contrast to inert systems, living biological systems have the advantage to adapt to their environment through growth and evolution. This transfiguration is evident during embryonic development, when the predisposed need to grow allows form to follow function. Alterations in the equilibrium state of biological systems breed disease and mutation in response to environmental triggers. The need to characterize the growth of biological systems to better understand these phenomena has motivated the continuum theory of growth and stimulated the development of computational tools in systems biology. Biological growth in development and disease is increasingly studied using the framework of morphoelasticity. Here, we demonstrate the potential for morphoelastic simulations through examples of volume, area, and length growth, inspired by tumor expansion, chronic bronchitis, brain development, intestine formation, plant shape, and myopia. We review the systems biology of living systems in light of biochemical and optical stimuli and classify different types of growth to facilitate the design of growth models for various biological systems within this generic framework. Exploring the systems biology of growth introduces a new venue to control and manipulate embryonic development, disease progression, and clinical intervention. © 2015 Wiley Periodicals, Inc.

The heparanome--the enigma of encoding and decoding heparan sulfate sulfation.

PubMed

Lamanna, William C; Kalus, Ina; Padva, Michael; Baldwin, Rebecca J; Merry, Catherine L R; Dierks, Thomas

2007-04-30

Heparan sulfate (HS) is a cell surface carbohydrate polymer modified with sulfate moieties whose highly ordered composition is central to directing specific cell signaling events. The ability of the cell to generate these information rich glycans with such specificity has opened up a new field of "heparanomics" which seeks to understand the systems involved in generating these cell type and developmental stage specific HS sulfation patterns. Unlike other instances where biological information is encrypted as linear sequences in molecules such as DNA, HS sulfation patterns are generated through a non-template driven process. Thus, deciphering the sulfation code and the dynamic nature of its generation has posed a new challenge to system biologists. The recent discovery of two sulfatases, Sulf1 and Sulf2, with the unique ability to edit sulfation patterns at the cell surface, has opened up a new dimension as to how we understand the regulation of HS sulfation patterning and pattern-dependent cell signaling events. This review will focus on the functional relationship between HS sulfation patterning and biological processes. Special attention will be given to Sulf1 and Sulf2 and how these key editing enzymes might act in concert with the HS biosynthetic enzymes to generate and regulate specific HS sulfation patterns in vivo. We will further explore the use of knock out mice as biological models for understanding the dynamic systems involved in generating HS sulfation patterns and their biological relevance. A brief overview of new technologies and innovations summarizes advances in the systems biology field for understanding non-template molecular networks and their influence on the "heparanome".

Macro- and microscale fluid flow systems for endothelial cell biology.

PubMed

Young, Edmond W K; Simmons, Craig A

2010-01-21

Recent advances in microfluidics have brought forth new tools for studying flow-induced effects on mammalian cells, with important applications in cardiovascular, bone and cancer biology. The plethora of microscale systems developed to date demonstrate the flexibility of microfluidic designs, and showcase advantages of the microscale that are simply not available at the macroscale. However, the majority of these systems will likely not achieve widespread use in the biological laboratory due to their complexity and lack of user-friendliness. To gain widespread acceptance in the biological research community, microfluidics engineers must understand the needs of cell biologists, while biologists must be made aware of available technology. This review provides a critical evaluation of cell culture flow (CCF) systems used to study the effects of mechanical forces on endothelial cells (ECs) in vitro. To help understand the need for various designs of CCF systems, we first briefly summarize main properties of ECs and their native environments. Basic principles of various macro- and microscale systems are described and evaluated. New opportunities are uncovered for developing technologies that have potential to both improve efficiency of experimentation as well as answer important biological questions that otherwise cannot be tackled with existing systems. Finally, we discuss some of the unresolved issues related to microfluidic cell culture, suggest possible avenues of investigation that could resolve these issues, and provide an outlook for the future of microfluidics in biological research.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Quantitative biology of single neurons

PubMed Central

Eberwine, James; Lovatt, Ditte; Buckley, Peter; Dueck, Hannah; Francis, Chantal; Kim, Tae Kyung; Lee, Jaehee; Lee, Miler; Miyashiro, Kevin; Morris, Jacqueline; Peritz, Tiina; Schochet, Terri; Spaethling, Jennifer; Sul, Jai-Yoon; Kim, Junhyong

2012-01-01

The building blocks of complex biological systems are single cells. Fundamental insights gained from single-cell analysis promise to provide the framework for understanding normal biological systems development as well as the limits on systems/cellular ability to respond to disease. The interplay of cells to create functional systems is not well understood. Until recently, the study of single cells has concentrated primarily on morphological and physiological characterization. With the application of new highly sensitive molecular and genomic technologies, the quantitative biochemistry of single cells is now accessible. PMID:22915636

Supporting Upper-Level Undergraduate Students in Building a Systems Perspective in a Botany Course

ERIC Educational Resources Information Center

Zangori, Laura; Koontz, Jason A.

2017-01-01

Undergraduate biology majors require biological literacy about the critical and dynamic relationships between plants and ecosystems and the effect human-made processes have on these systems. To support students in understanding systems relationships, we redesigned an undergraduate botany course using an ecological framework and embedded systems…

Systems Medicine: Sketching the Landscape.

PubMed

Kirschner, Marc

2016-01-01

To understand the meaning of the term Systems Medicine and to distinguish it from seemingly related other expressions currently in use, such as precision, personalized, -omics, or big data medicine, its underlying history and development into present time needs to be highlighted. Having this development in mind, it becomes evident that Systems Medicine is a genuine concept as well as a novel way of tackling the manifold complexity that occurs in nowadays clinical medicine-and not just a rebranding of what has previously been done in the past. So looking back it seems clear to many in the field that Systems Medicine has its origin in an integrative method to unravel biocomplexity, namely, Systems Biology. Here scientist by now gained useful experience that is on the verge toward implementation in clinical research and practice.Systems Medicine and Systems Biology have the same underlying theoretical principle in systems-based thinking-a methodology to understand complexity that can be traced back to ancient Greece. During the last decade, however, and due to a rapid methodological development in the life sciences and computing/IT technologies, Systems Biology has evolved from a scientific concept into an independent discipline most competent to tackle key questions of biocomplexity-with the potential to transform medicine and how it will be practiced in the future. To understand this process in more detail, the following section will thus give a short summary of the foundation of systems-based thinking and the different developmental stages including systems theory, the development of modern Systems Biology, and its transition into clinical practice. These are the components to pave the way toward Systems Medicine.

Holistic systems biology approaches to molecular mechanisms of human helper T cell differentiation to functionally distinct subsets.

PubMed

Chen, Z; Lönnberg, T; Lahesmaa, R

2013-08-01

Current knowledge of helper T cell differentiation largely relies on data generated from mouse studies. To develop therapeutical strategies combating human diseases, understanding the molecular mechanisms how human naïve T cells differentiate to functionally distinct T helper (Th) subsets as well as studies on human differentiated Th cell subsets is particularly valuable. Systems biology approaches provide a holistic view of the processes of T helper differentiation, enable discovery of new factors and pathways involved and generation of new hypotheses to be tested to improve our understanding of human Th cell differentiation and immune-mediated diseases. Here, we summarize studies where high-throughput systems biology approaches have been exploited to human primary T cells. These studies reveal new factors and signalling pathways influencing T cell differentiation towards distinct subsets, important for immune regulation. Such information provides new insights into T cell biology and into targeting immune system for therapeutic interventions. © 2013 John Wiley & Sons Ltd.

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aderem, Alan; Adkins, Joshua N.; Ansong, Charles

The 20th century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and water borne illnesses are frequent, multi-drug resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the 21st century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondinglymore » deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program we think that the time is at hand to redefine the pathogen-host research paradigm.« less

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

PubMed Central

Aderem, Alan; Adkins, Joshua N.; Ansong, Charles; Galagan, James; Kaiser, Shari; Korth, Marcus J.; Law, G. Lynn; McDermott, Jason G.; Proll, Sean C.; Rosenberger, Carrie; Schoolnik, Gary; Katze, Michael G.

2011-01-01

The twentieth century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and waterborne illnesses are frequent, multidrug-resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the twenty-first century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program, we think that the time is at hand to redefine the pathogen-host research paradigm. PMID:21285433

Network news: prime time for systems biology of the plant circadian clock.

PubMed

McClung, C Robertson; Gutiérrez, Rodrigo A

2010-12-01

Whole-transcriptome analyses have established that the plant circadian clock regulates virtually every plant biological process and most prominently hormonal and stress response pathways. Systems biology efforts have successfully modeled the plant central clock machinery and an iterative process of model refinement and experimental validation has contributed significantly to the current view of the central clock machinery. The challenge now is to connect this central clock to the output pathways for understanding how the plant circadian clock contributes to plant growth and fitness in a changing environment. Undoubtedly, systems approaches will be needed to integrate and model the vastly increased volume of experimental data in order to extract meaningful biological information. Thus, we have entered an era of systems modeling, experimental testing, and refinement. This approach, coupled with advances from the genetic and biochemical analyses of clock function, is accelerating our progress towards a comprehensive understanding of the plant circadian clock network. Copyright © 2010 Elsevier Ltd. All rights reserved.

Towards Biological Inspiration in the Development of Complex Systems

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Sterritt, Roy

2006-01-01

Greater understanding of biology in modem times has enabled significant breakthroughs in improving healthcare, quality of life, and eliminating many diseases and congenital illnesses. Simultaneously there is a move towards emulating nature and copying many of the wonders uncovered in biology, resulting in "biologically inspired" systems. Significant results have been reported in a wide range of areas, with systems inspired by nature enabling exploration, communication, and advances that were never dreamed possible just a few years ago. We warn, that as in many other fields of endeavor, we should be inspired by nature and biology, not engage in mimicry. We describe some results of biological inspiration that augur promise in terms of improving the safety and security of systems, and in developing self-managing systems, that we hope will ultimately lead to self-governing systems.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Evolving Relevance of Neuroproteomics in Alzheimer's Disease.

PubMed

Lista, Simone; Zetterberg, Henrik; O'Bryant, Sid E; Blennow, Kaj; Hampel, Harald

2017-01-01

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

Can a biologist fix a smartphone?-Just hack it!

PubMed

Kamoun, Sophien

2017-05-08

Biological systems integrate multiscale processes and networks and are, therefore, viewed as difficult to dissect. However, because of the clear-cut separation between the software code (the information encoded in the genome sequence) and hardware (organism), genome editors can operate as software engineers to hack biological systems without any particularly deep understanding of the complexity of the systems.

The Biology of Behaviour.

ERIC Educational Resources Information Center

Broom, D. M.

1981-01-01

Discusses topics to aid in understanding animal behavior, including the value of the biological approach to psychology, functional systems, optimality and fitness, universality of environmental effects on behavior, and evolution of social behavior. (DS)

Biological and Chemical Impact to Educational Facilities.

ERIC Educational Resources Information Center

Manicone, Santo

2002-01-01

Discusses preparing an educational facility to address the threat of biological or chemical terrorism, including understanding the potential impact, implementing information and communication systems, and improving medical surveillance and awareness. (EV)

Systems Approaches to Cancer Biology.

PubMed

Archer, Tenley C; Fertig, Elana J; Gosline, Sara J C; Hafner, Marc; Hughes, Shannon K; Joughin, Brian A; Meyer, Aaron S; Piccolo, Stephen R; Shajahan-Haq, Ayesha N

2016-12-01

Cancer systems biology aims to understand cancer as an integrated system of genes, proteins, networks, and interactions rather than an entity of isolated molecular and cellular components. The inaugural Systems Approaches to Cancer Biology Conference, cosponsored by the Association of Early Career Cancer Systems Biologists and the National Cancer Institute of the NIH, focused on the interdisciplinary field of cancer systems biology and the challenging cancer questions that are best addressed through the combination of experimental and computational analyses. Attendees found that elucidating the many molecular features of cancer inevitably reveals new forms of complexity and concluded that ensuring the reproducibility and impact of cancer systems biology studies will require widespread method and data sharing and, ultimately, the translation of important findings to the clinic. Cancer Res; 76(23); 6774-7. ©2016 AACR. ©2016 American Association for Cancer Research.

Growing trend of CE at the omics level: the frontier of systems biology--an update.

PubMed

Ban, Eunmi; Park, Soo Hyun; Kang, Min-Jung; Lee, Hyun-Jung; Song, Eun Joo; Yoo, Young Sook

2012-01-01

Omics is the study of proteins, peptides, genes, and metabolites in living organisms. Systems biology aims to understand the system through the study of the relationship between elements such as genes and proteins in biological system. Recently, systems biology emerged as the result of the advanced development of high-throughput analysis technologies such as DNA sequencers, DNA arrays, and mass spectrometry for omics studies. Among a number of analytical tools and technologies, CE and CE coupled to MS are promising and relatively rapidly developing tools with the potential to provide qualitative and quantitative analyses of biological molecules. With an emphasis on CE for systems biology, this review summarizes the method developments and applications of CE for the genomic, transcriptomic, proteomic, and metabolomic studies focusing on the drug discovery and disease diagnosis and therapies since 2009. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Biologist's Musing on Teaching about Entropy and Energy: Towards a Better Understanding of Life Processes

ERIC Educational Resources Information Center

Kattmann, Ulrich

2018-01-01

Should entropy and energy be emphasised as relevant concepts for biology education? This question will be discussed, highlighting the ways in which the concepts of entropy and energy can contribute to a better understanding of biological processes. Organisms are open systems. Therefore, the chosen perspective is different from the traditional…

Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines? What Really Constitutes the Study of "Systems Biology" and How Might Such an Approach Facilitate Vaccine Design.

PubMed

Germain, Ronald N

2017-10-16

A dichotomy exists in the field of vaccinology about the promise versus the hype associated with application of "systems biology" approaches to rational vaccine design. Some feel it is the only way to efficiently uncover currently unknown parameters controlling desired immune responses or discover what elements actually mediate these responses. Others feel that traditional experimental, often reductionist, methods for incrementally unraveling complex biology provide a more solid way forward, and that "systems" approaches are costly ways to collect data without gaining true insight. Here I argue that both views are inaccurate. This is largely because of confusion about what can be gained from classical experimentation versus statistical analysis of large data sets (bioinformatics) versus methods that quantitatively explain emergent properties of complex assemblies of biological components, with the latter reflecting what was previously called "physiology." Reductionist studies will remain essential for generating detailed insight into the functional attributes of specific elements of biological systems, but such analyses lack the power to provide a quantitative and predictive understanding of global system behavior. But by employing (1) large-scale screening methods for discovery of unknown components and connections in the immune system ( omics ), (2) statistical analysis of large data sets ( bioinformatics ), and (3) the capacity of quantitative computational methods to translate these individual components and connections into models of emergent behavior ( systems biology ), we will be able to better understand how the overall immune system functions and to determine with greater precision how to manipulate it to produce desired protective responses. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

Emerging systems biology approaches in nanotoxicology: Towards a mechanism-based understanding of nanomaterial hazard and risk

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Pedro M.; Fadeel, Bengt, E-mail: Bengt.Fade

Engineered nanomaterials are being developed for a variety of technological applications. However, the increasing use of nanomaterials in society has led to concerns about their potential adverse effects on human health and the environment. During the first decade of nanotoxicological research, the realization has emerged that effective risk assessment of the multitudes of new nanomaterials would benefit from a comprehensive understanding of their toxicological mechanisms, which is difficult to achieve with traditional, low-throughput, single end-point oriented approaches. Therefore, systems biology approaches are being progressively applied within the nano(eco)toxicological sciences. This novel paradigm implies that the study of biological systems shouldmore » be integrative resulting in quantitative and predictive models of nanomaterial behaviour in a biological system. To this end, global ‘omics’ approaches with which to assess changes in genes, proteins, metabolites, etc. are deployed allowing for computational modelling of the biological effects of nanomaterials. Here, we highlight omics and systems biology studies in nanotoxicology, aiming towards the implementation of a systems nanotoxicology and mechanism-based risk assessment of nanomaterials. - Highlights: • Systems nanotoxicology is a multi-disciplinary approach to quantitative modelling. • Transcriptomics, proteomics and metabolomics remain the most common methods. • Global “omics” techniques should be coupled to computational modelling approaches. • The discovery of nano-specific toxicity pathways and biomarkers is a prioritized goal. • Overall, experimental nanosafety research must endeavour reproducibility and relevance.« less

A Research Project-Based and Self-Determined Teaching System of Molecular Biology Techniques for Undergraduates

ERIC Educational Resources Information Center

Zhang, Shuping

2008-01-01

Molecular biology techniques play a very important role in understanding the biological activity. Students who major in biology should know not only how to perform experiments, but also the reasons for performing them. Having the concept of conducting research by integrating various techniques is especially important. This paper introduces a…

Chemical biology 2012: from drug targets to biological systems and back.

PubMed

Socher, Elke; Grossmann, Tom N

2013-01-02

Multiple sites sharing a common target: This year's EMBO conference on chemical biology encouraged over 340 researchers to come to Heidelberg, Germany, and discuss the use of diverse chemical strategies and tools to investigate biological questions and better understand cellular processes. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

Materiomics: biological protein materials, from nano to macro.

PubMed

Cranford, Steven; Buehler, Markus J

2010-11-12

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics - discovering Nature's complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature's materials have been hindered by our lack of fundamental understanding of these materials' intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure-property-process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering.

Materiomics: biological protein materials, from nano to macro

PubMed Central

Cranford, Steven; Buehler, Markus J

2010-01-01

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics – discovering Nature’s complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature’s materials have been hindered by our lack of fundamental understanding of these materials’ intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure–property–process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering. PMID:24198478

Peroxisystem: harnessing systems cell biology to study peroxisomes.

PubMed

Schuldiner, Maya; Zalckvar, Einat

2015-04-01

In recent years, high-throughput experimentation with quantitative analysis and modelling of cells, recently dubbed systems cell biology, has been harnessed to study the organisation and dynamics of simple biological systems. Here, we suggest that the peroxisome, a fascinating dynamic organelle, can be used as a good candidate for studying a complete biological system. We discuss several aspects of peroxisomes that can be studied using high-throughput systematic approaches and be integrated into a predictive model. Such approaches can be used in the future to study and understand how a more complex biological system, like a cell and maybe even ultimately a whole organism, works. © 2015 Société Française des Microscopies and Société de Biologie Cellulaire de France. Published by John Wiley & Sons Ltd.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2014-02-06

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology?

Advancing metabolic engineering through systems biology of industrial microorganisms.

PubMed

Dai, Zongjie; Nielsen, Jens

2015-12-01

Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further. Copyright © 2015 Elsevier Ltd. All rights reserved.

Systems medicine: a new approach to clinical practice.

PubMed

Cardinal-Fernández, Pablo; Nin, Nicolás; Ruíz-Cabello, Jesús; Lorente, José A

2014-10-01

Most respiratory diseases are considered complex diseases as their susceptibility and outcomes are determined by the interaction between host-dependent factors (genetic factors, comorbidities, etc.) and environmental factors (exposure to microorganisms or allergens, treatments received, etc.) The reductionist approach in the study of diseases has been of fundamental importance for the understanding of the different components of a system. Systems biology or systems medicine is a complementary approach aimed at analyzing the interactions between the different components within one organizational level (genome, transcriptome, proteome), and then between the different levels. Systems medicine is currently used for the interpretation and understanding of the pathogenesis and pathophysiology of different diseases, biomarker discovery, design of innovative therapeutic targets, and the drawing up of computational models for different biological processes. In this review we discuss the most relevant concepts of the theory underlying systems medicine, as well as its applications in the various biological processes in humans. Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

PubMed Central

Tyler, Anna L.; Asselbergs, Folkert W.; Williams, Scott M.; Moore, Jason H.

2011-01-01

Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena. PMID:19204994

Synthetic Biology: Engineering Living Systems from Biophysical Principles.

PubMed

Bartley, Bryan A; Kim, Kyung; Medley, J Kyle; Sauro, Herbert M

2017-03-28

Synthetic biology was founded as a biophysical discipline that sought explanations for the origins of life from chemical and physical first principles. Modern synthetic biology has been reinvented as an engineering discipline to design new organisms as well as to better understand fundamental biological mechanisms. However, success is still largely limited to the laboratory and transformative applications of synthetic biology are still in their infancy. Here, we review six principles of living systems and how they compare and contrast with engineered systems. We cite specific examples from the synthetic biology literature that illustrate these principles and speculate on their implications for further study. To fully realize the promise of synthetic biology, we must be aware of life's unique properties. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Two sides of the same coin? The (techno)epistemic cultures of systems and synthetic biology.

PubMed

Kastenhofer, Karen

2013-06-01

Systems and synthetic biology both emerged around the turn of this century as labels for new research approaches. Although their disciplinary status as well as their relation to each other is rarely discussed in depth, now and again the idea is invoked that both approaches represent 'two sides of the same coin'. The following paper focuses on this general notion and compares it with empirical findings concerning the epistemic cultures prevalent in the two contexts. Drawing on interviews with researchers from both fields, on participatory observation in conferences and courses and on documentary analysis, this paper delineates differences and similarities, incompatibilities and blurred boundaries. By reconstructing systems and synthetic biology's epistemic cultures, this paper argues that they represent two 'communities of vision', encompassing heterogeneous practices. Understanding the relation of the respective visions of understanding nature and engineering life is seen as indispensible for the characterisation of (techno)science in more general terms. Depending on the conceptualisation of understanding and construction (or: science and engineering), related practices such as in silico modelling for enhancing understanding or enabling engineering can either be seen as incommensurable or 'two sides of one coin'. Copyright © 2013 Elsevier Ltd. All rights reserved.

The art of curation at a biological database: principles and application

USDA-ARS?s Scientific Manuscript database

The variety and quantity of data being produced by biological research has grown dramatically in recent years, resulting in an expansion of our understanding of biological systems. However, this abundance of data has brought new challenges, especially in curation. The role of biocurators is in part ...

The Effects of Explicit Visual Cues in Reading Biological Diagrams

ERIC Educational Resources Information Center

Ge, Yun-Ping; Unsworth, Len; Wang, Kuo-Hua

2017-01-01

Drawing on cognitive theories, this study intends to investigate the effects of explicit visual cues which have been proposed as a critical factor in facilitating understanding of biological images. Three diagrams from Taiwanese textbooks with implicit visual cues, involving the concepts of biological classification systems, fish taxonomy, and…

Morphomics: An integral part of systems biology of the human placenta.

PubMed

Mayhew, T M

2015-04-01

The placenta is a transient organ the functioning of which has health consequences far beyond the embryo/fetus. Understanding the biology of any system (organ, organism, single cell, etc) requires a comprehensive and inclusive approach which embraces all the biomedical disciplines and 'omic' technologies and then integrates information obtained from all of them. Among the latest 'omics' is morphomics. The terms morphome and morphomics have been applied incoherently in biology and biomedicine but, recently, they have been given clear and widescale definitions. Morphomics is placed in the context of other 'omics' and its pertinent technologies and tools for sampling and quantitation are reviewed. Emphasis is accorded to the importance of random sampling principles in systems biology and the value of combining 3D quantification with alternative imaging techniques to advance knowledge and understanding of the human placental morphome. By analogy to other 'omes', the morphome is the totality of morphological features within a system and morphomics is the systematic study of those structures. Information about structure is required at multiple levels of resolution in order to understand better the processes by which a given system alters with time, experimental treatment or environmental insult. Therefore, morphomics research includes all imaging techniques at all levels of achievable resolution from gross anatomy and medical imaging, via optical and electron microscopy, to molecular characterisation. Quantification is an important element of all 'omics' studies and, because biological systems exist and operate in 3-dimensional (3D) space, precise descriptions of form, content and spatial relationships require the quantification of structure in 3D. These considerations are relevant to future study contributions to the Human Placenta Project. Copyright © 2015 Elsevier Ltd. All rights reserved.

Systems biology of eukaryotic superorganisms and the holobiont concept.

PubMed

Kutschera, Ulrich

2018-06-14

The founders of modern biology (Jean Lamarck, Charles Darwin, August Weismann etc.) were organismic life scientists who attempted to understand the morphology and evolution of living beings as a whole (i.e., the phenotype). However, with the emergence of the study of animal and plant physiology in the nineteenth century, this "holistic view" of the living world changed and was ultimately replaced by a reductionistic perspective. Here, I summarize the history of systems biology, i.e., the modern approach to understand living beings as integrative organisms, from genotype to phenotype. It is documented that the physiologists Claude Bernard and Julius Sachs, who studied humans and plants, respectively, were early pioneers of this discipline, which was formally founded 50 years ago. In 1968, two influential monographs, authored by Ludwig von Bertalanffy and Mihajlo D. Mesarović, were published, wherein a "systems theory of biology" was outlined. Definitions of systems biology are presented with reference to metabolic or cell signaling networks, analyzed via genomics, proteomics, and other methods, combined with computer simulations/mathematical modeling. Then, key insights of this discipline with respect to epiphytic microbes (Methylobacterium sp.) and simple bacteria (Mycoplasma sp.) are described. The principles of homeostasis, molecular systems energetics, gnotobiology, and holobionts (i.e., complexities of host-microbiota interactions) are outlined, and the significance of systems biology for evolutionary theories is addressed. Based on the microbe-Homo sapiens-symbiosis, it is concluded that human biology and health should be interpreted in light of a view of the biomedical sciences that is based on the holobiont concept.

Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology.

PubMed

Barah, Pankaj; Bones, Atle M

2015-02-01

The biggest challenge for modern biology is to integrate multidisciplinary approaches towards understanding the organizational and functional complexity of biological systems at different hierarchies, starting from the subcellular molecular mechanisms (microscopic) to the functional interactions of ecological communities (macroscopic). The plant-insect interaction is a good model for this purpose with the availability of an enormous amount of information at the molecular and the ecosystem levels. Changing global climatic conditions are abruptly resetting plant-insect interactions. Integration of discretely located heterogeneous information from the ecosystem to genes and pathways will be an advantage to understand the complexity of plant-insect interactions. This review will present the recent developments in omics-based high-throughput experimental approaches, with particular emphasis on studying plant defence responses against insect attack. The review highlights the importance of using integrative systems approaches to study plant-insect interactions from the macroscopic to the microscopic level. We analyse the current efforts in generating, integrating and modelling multiomics data to understand plant-insect interaction at a systems level. As a future prospect, we highlight the growing interest in utilizing the synthetic biology platform for engineering insect-resistant plants. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Systems Biology in Immunology – A Computational Modeling Perspective

PubMed Central

Germain, Ronald N.; Meier-Schellersheim, Martin; Nita-Lazar, Aleksandra; Fraser, Iain D. C.

2011-01-01

Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and conduct simulations of immune function, We provide descriptions of the key data gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease. PMID:21219182

Metabolomics: Definitions and Significance in Systems Biology.

PubMed

Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

2017-01-01

Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

Exploring biology with small organic molecules

PubMed Central

Stockwell, Brent R.

2011-01-01

Small organic molecules have proven to be invaluable tools for investigating biological systems, but there is still much to learn from their use. To discover and to use more effectively new chemical tools to understand biology, strategies are needed that allow us to systematically explore ‘biological-activity space’. Such strategies involve analysing both protein binding of, and phenotypic responses to, small organic molecules. The mapping of biological-activity space using small molecules is akin to mapping the stars — uncharted territory is explored using a system of coordinates that describes where each new feature lies. PMID:15602550

Systems Modelling and the Development of Coherent Understanding of Cell Biology

ERIC Educational Resources Information Center

Verhoeff, Roald P.; Waarlo, Arend Jan; Boersma, Kerst Th.

2008-01-01

This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing "systems modelling" as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of free-living cells, a general two-dimensional model of…

Information processing in bacteria: memory, computation, and statistical physics: a key issues review

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network—the main players (nodes) and their interactions (links)—in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review.

PubMed

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network-the main players (nodes) and their interactions (links)-in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

The genotype-phenotype map of an evolving digital organism.

PubMed

Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism

PubMed Central

Zaman, Luis; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable. PMID:28241039

Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology.

PubMed

Weckwerth, Wolfram

2011-12-10

Plants have shaped our human life form from the outset. With the emerging recognition of world population feeding, global climate change and limited energy resources with fossil fuels, the relevance of plant biology and biotechnology is becoming dramatically important. One key issue is to improve plant productivity and abiotic/biotic stress resistance in agriculture due to restricted land area and increasing environmental pressures. Another aspect is the development of CO(2)-neutral plant resources for fiber/biomass and biofuels: a transition from first generation plants like sugar cane, maize and other important nutritional crops to second and third generation energy crops such as Miscanthus and trees for lignocellulose and algae for biomass and feed, hydrogen and lipid production. At the same time we have to conserve and protect natural diversity and species richness as a foundation of our life on earth. Here, biodiversity banks are discussed as a foundation of current and future plant breeding research. Consequently, it can be anticipated that plant biology and ecology will have more indispensable future roles in all socio-economic aspects of our life than ever before. We therefore need an in-depth understanding of the physiology of single plant species for practical applications as well as the translation of this knowledge into complex natural as well as anthropogenic ecosystems. Latest developments in biological and bioanalytical research will lead into a paradigm shift towards trying to understand organisms at a systems level and in their ecosystemic context: (i) shotgun and next-generation genome sequencing, gene reconstruction and annotation, (ii) genome-scale molecular analysis using OMICS technologies and (iii) computer-assisted analysis, modeling and interpretation of biological data. Systems biology combines these molecular data, genetic evolution, environmental cues and species interaction with the understanding, modeling and prediction of active biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted 'omic' technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems - plants, fungi, animals and bacteria - will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype-phenotype environment relationship as the fundamental drivers of ecology and evolution. Copyright © 2011 Elsevier B.V. All rights reserved.

You can exercise your way out of HIV and other stories: The role of biological knowledge in adolescents' evaluation of myths

NASA Astrophysics Data System (ADS)

Keselman, Alla; Kaufman, David R.; Patel, Vimla L.

2004-07-01

A primary objective for science education is to impart robust knowledge that has applicability to real-world problems. This article presents research investigating the relationship between adolescents' conceptual understanding of the biological basis of HIV and critical reasoning. Middle and high school students were interviewed about their understanding of HIV and were subsequently asked to evaluate scenarios that contained myths about HIV. On the basis of their responses to the interview questions, students' understanding of HIV was categorized into three models, naïve, intermediate, and advanced. The results indicate that knowledge mediated students' responses in specific ways. Students at different levels of HIV knowledge reasoned in qualitatively different ways about the myths. A significant relationship was found between students' understanding of HIV biology and the level of biological reasoning. We found that students who employed cellular-level biological reasoning were more likely to reject the myths than students who employed just system-level reasoning or nonspecific biological reasoning. The findings emphasize the importance of conceptual understanding in the critical evaluation of information that may serve as a basis for making decisions about HIV. We conclude with discussing the implications of the findings for science and health education.

Biological robustness.

PubMed

Kitano, Hiroaki

2004-11-01

Robustness is a ubiquitously observed property of biological systems. It is considered to be a fundamental feature of complex evolvable systems. It is attained by several underlying principles that are universal to both biological organisms and sophisticated engineering systems. Robustness facilitates evolvability and robust traits are often selected by evolution. Such a mutually beneficial process is made possible by specific architectural features observed in robust systems. But there are trade-offs between robustness, fragility, performance and resource demands, which explain system behaviour, including the patterns of failure. Insights into inherent properties of robust systems will provide us with a better understanding of complex diseases and a guiding principle for therapy design.

Understanding Global Change (UGC) as a Unifying Conceptual Framework for Teaching Ecology: Using UGC in a High School Biology Program to Integrate Earth Science and Biology, and to Demonstrate the Value of Modeling Global Systems in Promoting Conceptual Learning

NASA Astrophysics Data System (ADS)

Levine, J.; Bean, J. R.

2017-12-01

Global change science is ideal for NGSS-informed teaching, but presents a serious challenge to K-12 educators because it is complex and interdisciplinary- combining earth science, biology, chemistry, and physics. Global systems are themselves complex. Adding anthropogenic influences on those systems creates a formidable list of topics - greenhouse effect, climate change, nitrogen enrichment, introduced species, land-use change among them - which are often presented as a disconnected "laundry list" of "facts." This complexity, combined with public and mass-media scientific illiteracy, leaves global change science vulnerable to misrepresentation and politicization, creating additional challenges to teachers in public schools. Ample stand-alone, one-off, online resources, many of them excellent, are (to date) underutilized by teachers in the high school science course taken by most students: biology. The Understanding Global Change project (UGC) from the UC Berkeley Museum of Paleontology has created a conceptual framework that organizes, connects, and explains global systems, human and non-human drivers of change in those systems, and measurable changes in those systems. This organization and framework employ core ideas, crosscutting concepts, structure/function relationships, and system models in a unique format that facilitates authentic understanding, rather than memorization. This system serves as an organizing framework for the entire ecology unit of a forthcoming mainstream high school biology program. The UGC system model is introduced up front with its core informational graphic. The model is elaborated, step by step, by adding concepts and processes as they are introduced and explained in each chapter. The informational graphic is thus used in several ways: to organize material as it is presented, to summarize topics in each chapter and put them in perspective, and for review and critical thinking exercises that supplement the usual end-of-chapter lists of key terms.

Dietary antioxidant synergy in chemical and biological systems.

PubMed

Wang, Sunan; Zhu, Fan

2017-07-24

Antioxidant (AOX) synergies have been much reported in chemical ("test-tube" based assays focusing on pure chemicals), biological (tissue culture, animal and clinical models), and food systems during the past decade. Tentative synergies differ from each other due to the composition of AOX and the quantification methods. Regeneration mechanism responsible for synergy in chemical systems has been discussed. Solvent effects could contribute to the artifacts of synergy observed in the chemical models. Synergy in chemical models may hardly be relevant to biological systems that have been much less studied. Apparent discrepancies exist in understanding the molecular mechanisms in both chemical and biological systems. This review discusses diverse variables associated with AOX synergy and molecular scenarios for explanation. Future research to better utilize the synergy is suggested.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges

PubMed Central

Villaverde, Alejandro F.; Banga, Julio R.

2014-01-01

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology? PMID:24307566

Systems biology of human atherosclerosis.

PubMed

Shalhoub, Joseph; Sikkel, Markus B; Davies, Kerry J; Vorkas, Panagiotis A; Want, Elizabeth J; Davies, Alun H

2014-01-01

Systems biology describes a holistic and integrative approach to understand physiology and pathology. The "omic" disciplines include genomics, transcriptomics, proteomics, and metabolic profiling (metabonomics and metabolomics). By adopting a stance, which is opposing (yet complimentary) to conventional research techniques, systems biology offers an overview by assessing the "net" biological effect imposed by a disease or nondisease state. There are a number of different organizational levels to be understood, from DNA to protein, metabolites, cells, organs and organisms, even beyond this to an organism's context. Systems biology relies on the existence of "nodes" and "edges." Nodes are the constituent part of the system being studied (eg, proteins in the proteome), while the edges are the way these constituents interact. In future, it will be increasingly important to collaborate, collating data from multiple studies to improve data sets, making them freely available and undertaking integrative analyses.

Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

PubMed

Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-03-01

"A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

Systems biology-based approaches toward understanding drought tolerance in food crops.

PubMed

Jogaiah, Sudisha; Govind, Sharathchandra Ramsandra; Tran, Lam-Son Phan

2013-03-01

Economically important crops, such as maize, wheat, rice, barley, and other food crops are affected by even small changes in water potential at important growth stages. Developing a comprehensive understanding of host response to drought requires a global view of the complex mechanisms involved. Research on drought tolerance has generally been conducted using discipline-specific approaches. However, plant stress response is complex and interlinked to a point where discipline-specific approaches do not give a complete global analysis of all the interlinked mechanisms. Systems biology perspective is needed to understand genome-scale networks required for building long-lasting drought resistance. Network maps have been constructed by integrating multiple functional genomics data with both model plants, such as Arabidopsis thaliana, Lotus japonicus, and Medicago truncatula, and various food crops, such as rice and soybean. Useful functional genomics data have been obtained from genome-wide comparative transcriptome and proteome analyses of drought responses from different crops. This integrative approach used by many groups has led to identification of commonly regulated signaling pathways and genes following exposure to drought. Combination of functional genomics and systems biology is very useful for comparative analysis of other food crops and has the ability to develop stable food systems worldwide. In addition, studying desiccation tolerance in resurrection plants will unravel how combination of molecular genetic and metabolic processes interacts to produce a resurrection phenotype. Systems biology-based approaches have helped in understanding how these individual factors and mechanisms (biochemical, molecular, and metabolic) "interact" spatially and temporally. Signaling network maps of such interactions are needed that can be used to design better engineering strategies for improving drought tolerance of important crop species.

Modeling formalisms in Systems Biology

PubMed Central

2011-01-01

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future. PMID:22141422

Web-based software tool for constraint-based design specification of synthetic biological systems.

PubMed

Oberortner, Ernst; Densmore, Douglas

2015-06-19

miniEugene provides computational support for solving combinatorial design problems, enabling users to specify and enumerate designs for novel biological systems based on sets of biological constraints. This technical note presents a brief tutorial for biologists and software engineers in the field of synthetic biology on how to use miniEugene. After reading this technical note, users should know which biological constraints are available in miniEugene, understand the syntax and semantics of these constraints, and be able to follow a step-by-step guide to specify the design of a classical synthetic biological system-the genetic toggle switch.1 We also provide links and references to more information on the miniEugene web application and the integration of the miniEugene software library into sophisticated Computer-Aided Design (CAD) tools for synthetic biology ( www.eugenecad.org ).

From the Director: The Joy of Science, the Courage of Research

MedlinePlus

... Dr. Zerhouni , one that combines an appreciation of biological complexity with the fearless search for scientific knowledge. ... techniques for greater understanding of the complexity of biological systems. The one thing that has driven my ...

Biocharts: a visual formalism for complex biological systems

PubMed Central

Kugler, Hillel; Larjo, Antti; Harel, David

2010-01-01

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis. PMID:20022895

Industrial systems biology and its impact on synthetic biology of yeast cell factories.

PubMed

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-06-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Neural system modeling and simulation using Hybrid Functional Petri Net.

PubMed

Tang, Yin; Wang, Fei

2012-02-01

The Petri net formalism has been proved to be powerful in biological modeling. It not only boasts of a most intuitive graphical presentation but also combines the methods of classical systems biology with the discrete modeling technique. Hybrid Functional Petri Net (HFPN) was proposed specially for biological system modeling. An array of well-constructed biological models using HFPN yielded very interesting results. In this paper, we propose a method to represent neural system behavior, where biochemistry and electrical chemistry are both included using the Petri net formalism. We built a model for the adrenergic system using HFPN and employed quantitative analysis. Our simulation results match the biological data well, showing that the model is very effective. Predictions made on our model further manifest the modeling power of HFPN and improve the understanding of the adrenergic system. The file of our model and more results with their analysis are available in our supplementary material.

Mechanochemical cell biology.

PubMed

Cross, R A; McAinsh, A D; Straube, A

2011-12-01

Eukaryotic systems self-organise by using molecular railways to shuttle specific sets of molecular components to specific locations. In this way, cells are enabled to become larger, more complex and more varied, subtle and effective in their activities. Because of the fundamental importance of molecular railways in eukaryotic systems, understanding how these railways work is an important research goal. Mechanochemical cell biology is a newly circumscribed subject area that concerns itself with the molecular and cell biological mechanisms of motorised directional transport in living systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

The painted turtle, Chrysemys picta: a model system for vertebrate evolution, ecology, and human health.

PubMed

Valenzuela, Nicole

2009-07-01

Painted turtles (Chrysemys picta) are representatives of a vertebrate clade whose biology and phylogenetic position hold a key to our understanding of fundamental aspects of vertebrate evolution. These features make them an ideal emerging model system. Extensive ecological and physiological research provide the context in which to place new research advances in evolutionary genetics, genomics, evolutionary developmental biology, and ecological developmental biology which are enabled by current resources, such as a bacterial artificial chromosome (BAC) library of C. picta, and the imminent development of additional ones such as genome sequences and cDNA and expressed sequence tag (EST) libraries. This integrative approach will allow the research community to continue making advances to provide functional and evolutionary explanations for the lability of biological traits found not only among reptiles but vertebrates in general. Moreover, because humans and reptiles share a common ancestor, and given the ease of using nonplacental vertebrates in experimental biology compared with mammalian embryos, painted turtles are also an emerging model system for biomedical research. For example, painted turtles have been studied to understand many biological responses to overwintering and anoxia, as potential sentinels for environmental xenobiotics, and as a model to decipher the ecology and evolution of sexual development and reproduction. Thus, painted turtles are an excellent reptilian model system for studies with human health, environmental, ecological, and evolutionary significance.

‘Integrative Physiology 2.0’: integration of systems biology into physiology and its application to cardiovascular homeostasis

PubMed Central

Kuster, Diederik W D; Merkus, Daphne; van der Velden, Jolanda; Verhoeven, Adrie J M; Duncker, Dirk J

2011-01-01

Since the completion of the Human Genome Project and the advent of the large scaled unbiased ‘-omics’ techniques, the field of systems biology has emerged. Systems biology aims to move away from the traditional reductionist molecular approach, which focused on understanding the role of single genes or proteins, towards a more holistic approach by studying networks and interactions between individual components of networks. From a conceptual standpoint, systems biology elicits a ‘back to the future’ experience for any integrative physiologist. However, many of the new techniques and modalities employed by systems biologists yield tremendous potential for integrative physiologists to expand their tool arsenal to (quantitatively) study complex biological processes, such as cardiac remodelling and heart failure, in a truly holistic fashion. We therefore advocate that systems biology should not become/stay a separate discipline with ‘-omics’ as its playing field, but should be integrated into physiology to create ‘Integrative Physiology 2.0’. PMID:21224228

Advanced systems biology methods in drug discovery and translational biomedicine.

PubMed

Zou, Jun; Zheng, Ming-Wu; Li, Gen; Su, Zhi-Guang

2013-01-01

Systems biology is in an exponential development stage in recent years and has been widely utilized in biomedicine to better understand the molecular basis of human disease and the mechanism of drug action. Here, we discuss the fundamental concept of systems biology and its two computational methods that have been commonly used, that is, network analysis and dynamical modeling. The applications of systems biology in elucidating human disease are highlighted, consisting of human disease networks, treatment response prediction, investigation of disease mechanisms, and disease-associated gene prediction. In addition, important advances in drug discovery, to which systems biology makes significant contributions, are discussed, including drug-target networks, prediction of drug-target interactions, investigation of drug adverse effects, drug repositioning, and drug combination prediction. The systems biology methods and applications covered in this review provide a framework for addressing disease mechanism and approaching drug discovery, which will facilitate the translation of research findings into clinical benefits such as novel biomarkers and promising therapies.

2016 Summer Series - Michael Flynn - Synthetic Biological Membrane

NASA Image and Video Library

2016-08-02

Full understanding leads to creation capability, which results in customization capacity. Synthetic biology uses our knowledge of biology to engineer novel biological devices or organisms that can perform tasks not found in nature. For Human space exploration, synthetic biology approaches will reduce risk, mass carried and increase Human reach. Michael Flynn will discuss the International Space Station (ISS) water recycling and his current work on developing a water filtration system capable of self-repair.

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Analyzing Defects in the "Caenorhabditis Elegans" Nervous System Using Organismal and Cell Biological Approaches

ERIC Educational Resources Information Center

Guziewicz, Megan; Vitullo, Toni; Simmons, Bethany; Kohn, Rebecca Eustance

2002-01-01

The goal of this laboratory exercise is to increase student understanding of the impact of nervous system function at both the organismal and cellular levels. This inquiry-based exercise is designed for an undergraduate course examining principles of cell biology. After observing the movement of "Caenorhabditis elegans" with defects in their…

The mammary gland in domestic ruminants: a systems biology perspective.

PubMed

Ferreira, Ana M; Bislev, Stine L; Bendixen, Emøke; Almeida, André M

2013-12-06

Milk and dairy products are central elements in the human diet. It is estimated that 108kg of milk per year are consumed per person worldwide. Therefore, dairy production represents a relevant fraction of the economies of many countries, being cattle, sheep, goat, water buffalo, and other ruminants the main species used worldwide. An adequate management of dairy farming cannot be achieved without the knowledge on the biological mechanisms behind lactation in ruminants. Thus, understanding the morphology, development and regulation of the mammary gland in health, disease and production is crucial. Presently, innovative and high-throughput technologies such as genomics, transcriptomics, proteomics and metabolomics allow a much broader and detailed knowledge on such issues. Additionally, the application of a systems biology approach to animal science is vastly growing, as new advances in one field of specialization or animal species lead to new lines of research in other areas or/and are expanded to other species. This article addresses how modern research approaches may help us understand long-known issues in mammary development, lactation biology and dairy production. Dairy production depends upon the knowledge of the morphology and regulation of the mammary gland and lactation. High-throughput technologies allow a much broader and detailed knowledge on the biology of the mammary gland. This paper reviews the major contributions that genomics, transcriptomics, metabolomics and proteomics approaches have provided to understand the regulation of the mammary gland in health, disease and production. In the context of mammary gland "omics"-based research, the integration of results using a Systems Biology Approach is of key importance. © 2013.

Coupling biology and oceanography in models.

PubMed

Fennel, W; Neumann, T

2001-08-01

The dynamics of marine ecosystems, i.e. the changes of observable chemical-biological quantities in space and time, are driven by biological and physical processes. Predictions of future developments of marine systems need a theoretical framework, i.e. models, solidly based on research and understanding of the different processes involved. The natural way to describe marine systems theoretically seems to be the embedding of chemical-biological models into circulation models. However, while circulation models are relatively advanced the quantitative theoretical description of chemical-biological processes lags behind. This paper discusses some of the approaches and problems in the development of consistent theories and indicates the beneficial potential of the coupling of marine biology and oceanography in models.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Dupuytren's: a systems biology disease

PubMed Central

2011-01-01

Dupuytren's disease (DD) is an ill-defined fibroproliferative disorder of the palm of the hands leading to digital contracture. DD commonly occurs in individuals of northern European extraction. Cellular components and processes associated with DD pathogenesis include altered gene and protein expression of cytokines, growth factors, adhesion molecules, and extracellular matrix components. Histology has shown increased but varying levels of particular types of collagen, myofibroblasts and myoglobin proteins in DD tissue. Free radicals and localised ischaemia have been suggested to trigger the proliferation of DD tissue. Although the existing available biological information on DD may contain potentially valuable (though largely uninterpreted) information, the precise aetiology of DD remains unknown. Systems biology combines mechanistic modelling with quantitative experimentation in studies of networks and better understanding of the interaction of multiple components in disease processes. Adopting systems biology may be the ideal approach for future research in order to improve understanding of complex diseases of multifactorial origin. In this review, we propose that DD is a disease of several networks rather than of a single gene, and show that this accounts for the experimental observations obtained to date from a variety of sources. We outline how DD may be investigated more effectively by employing a systems biology approach that considers the disease network as a whole rather than focusing on any specific single molecule. PMID:21943049

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

Using synthetic biology to make cells tomorrow's test tubes.

PubMed

Garcia, Hernan G; Brewster, Robert C; Phillips, Rob

2016-04-18

The main tenet of physical biology is that biological phenomena can be subject to the same quantitative and predictive understanding that physics has afforded in the context of inanimate matter. However, the inherent complexity of many of these biological processes often leads to the derivation of complex theoretical descriptions containing a plethora of unknown parameters. Such complex descriptions pose a conceptual challenge to the establishment of a solid basis for predictive biology. In this article, we present various exciting examples of how synthetic biology can be used to simplify biological systems and distill these phenomena down to their essential features as a means to enable their theoretical description. Here, synthetic biology goes beyond previous efforts to engineer nature and becomes a tool to bend nature to understand it. We discuss various recent and classic experiments featuring applications of this synthetic approach to the elucidation of problems ranging from bacteriophage infection, to transcriptional regulation in bacteria and in developing embryos, to evolution. In all of these examples, synthetic biology provides the opportunity to turn cells into the equivalent of a test tube, where biological phenomena can be reconstituted and our theoretical understanding put to test with the same ease that these same phenomena can be studied in the in vitro setting.

Digital biology and chemistry.

PubMed

Witters, Daan; Sun, Bing; Begolo, Stefano; Rodriguez-Manzano, Jesus; Robles, Whitney; Ismagilov, Rustem F

2014-09-07

This account examines developments in "digital" biology and chemistry within the context of microfluidics, from a personal perspective. Using microfluidics as a frame of reference, we identify two areas of research within digital biology and chemistry that are of special interest: (i) the study of systems that switch between discrete states in response to changes in chemical concentration of signals, and (ii) the study of single biological entities such as molecules or cells. In particular, microfluidics accelerates analysis of switching systems (i.e., those that exhibit a sharp change in output over a narrow range of input) by enabling monitoring of multiple reactions in parallel over a range of concentrations of signals. Conversely, such switching systems can be used to create new kinds of microfluidic detection systems that provide "analog-to-digital" signal conversion and logic. Microfluidic compartmentalization technologies for studying and isolating single entities can be used to reconstruct and understand cellular processes, study interactions between single biological entities, and examine the intrinsic heterogeneity of populations of molecules, cells, or organisms. Furthermore, compartmentalization of single cells or molecules in "digital" microfluidic experiments can induce switching in a range of reaction systems to enable sensitive detection of cells or biomolecules, such as with digital ELISA or digital PCR. This "digitizing" offers advantages in terms of robustness, assay design, and simplicity because quantitative information can be obtained with qualitative measurements. While digital formats have been shown to improve the robustness of existing chemistries, we anticipate that in the future they will enable new chemistries to be used for quantitative measurements, and that digital biology and chemistry will continue to provide further opportunities for measuring biomolecules, understanding natural systems more deeply, and advancing molecular and cellular analysis. Microfluidics will impact digital biology and chemistry and will also benefit from them if it becomes massively distributed.

Dynamics of problem setting and framing in citizen discussions on synthetic biology.

PubMed

Betten, Afke Wieke; Broerse, Jacqueline E W; Kupper, Frank

2018-04-01

Synthetic biology is an emerging scientific field where engineers and biologists design and build biological systems for various applications. Developing synthetic biology responsibly in the public interest necessitates a meaningful societal dialogue. In this article, we argue that facilitating such a dialogue requires an understanding of how people make sense of synthetic biology. We performed qualitative research to unravel the underlying dynamics of problem setting and framing in citizen discussions on synthetic biology. We found that most people are not inherently for or against synthetic biology as a technology or development in itself, but that their perspectives are framed by core values about our relationships with science and technology and that sensemaking is much dependent on the context and general feelings of (dis)content. Given that there are many assumptions focused on a more binary idea of the public's view, we emphasize the need for frame awareness and understanding in a meaningful dialogue.

System approaches of Weiss and Bertalanffy and their relevance for systems biology today.

PubMed

Drack, Manfred; Wolkenhauer, Olaf

2011-06-01

System approaches in biology have a long history. We focus here on the thinking of Paul A. Weiss and Ludwig von Bertalanffy, who contributed a great deal towards making the system concept operable in biology in the early 20th century. To them, considering whole living systems, which includes their organisation or order, is equally important as the dynamics within systems and the interplay between different levels from molecules over cells to organisms. They also called for taking the intrinsic activity of living systems and the conservation of system states into account. We compare these notions with today's systems biology, which is often a bottom-up approach from molecular dynamics to cellular behaviour. We conclude that bringing together the early heuristics with recent formalisms and novel experimental set-ups can lead to fruitful results and understanding. Copyright © 2011 Elsevier Ltd. All rights reserved.

Systems Vaccinology: Enabling rational vaccine design with systems biological approaches

PubMed Central

Hagan, Thomas; Nakaya, Helder I.; Subramaniam, Shankar; Pulendran, Bali

2015-01-01

Vaccines have drastically reduced the mortality and morbidity of many diseases. However, vaccines have historically been developed empirically, and recent development of vaccines against current pandemics such as HIV and malaria has been met with difficulty. The advent of high-throughput technologies, coupled with systems biological methods of data analysis, has enabled researchers to interrogate the entire complement of a variety of molecular components within cells, and characterize the myriad interactions among them in order to model and understand the behavior of the system as a whole. In the context of vaccinology, these tools permit exploration of the molecular mechanisms by which vaccines induce protective immune responses. Here we review the recent advances, challenges, and potential of systems biological approaches in vaccinology. If the challenges facing this developing field can be overcome, systems vaccinology promises to empower the identification of early predictive signatures of vaccine response, as well as novel and robust correlates of protection from infection. Such discoveries, along with the improved understanding of immune responses to vaccination they impart, will play an instrumental role in development of the next generation of rationally designed vaccines. PMID:25858860

Normal morphogenesis of epithelial tissues and progression of epithelial tumors

PubMed Central

Wang, Chun-Chao; Jamal, Leen; Janes, Kevin A.

2011-01-01

Epithelial cells organize into various tissue architectures that largely maintain their structure throughout the life of an organism. For decades, the morphogenesis of epithelial tissues has fascinated scientists at the interface of cell, developmental, and molecular biology. Systems biology offers ways to combine knowledge from these disciplines by building integrative models that are quantitative and predictive. Can such models be useful for gaining a deeper understanding of epithelial morphogenesis? Here, we take inventory of some recurring themes in epithelial morphogenesis that systems approaches could strive to capture. Predictive understanding of morphogenesis at the systems level would prove especially valuable for diseases such as cancer, where epithelial tissue architecture is profoundly disrupted. PMID:21898857

Molecular dynamics simulations and applications in computational toxicology and nanotoxicology.

PubMed

Selvaraj, Chandrabose; Sakkiah, Sugunadevi; Tong, Weida; Hong, Huixiao

2018-02-01

Nanotoxicology studies toxicity of nanomaterials and has been widely applied in biomedical researches to explore toxicity of various biological systems. Investigating biological systems through in vivo and in vitro methods is expensive and time taking. Therefore, computational toxicology, a multi-discipline field that utilizes computational power and algorithms to examine toxicology of biological systems, has gained attractions to scientists. Molecular dynamics (MD) simulations of biomolecules such as proteins and DNA are popular for understanding of interactions between biological systems and chemicals in computational toxicology. In this paper, we review MD simulation methods, protocol for running MD simulations and their applications in studies of toxicity and nanotechnology. We also briefly summarize some popular software tools for execution of MD simulations. Published by Elsevier Ltd.

Will systems biology offer new holistic paradigms to life sciences?

PubMed Central

Conti, Filippo; Valerio, Maria Cristina; Zbilut, Joseph P.

2008-01-01

A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms. PMID:19003440

Basic Energy Science | NREL

Science.gov Websites

scientific understanding-of molecular, nanoscale, semiconductor, and biological materials, systems, and molecular, nanoscale, and semiconductor systems to capture, control, and convert solar radiation with high

C. elegans network biology: a beginning.

PubMed Central

Piano, Fabio; Gunsalus, Kristin C; Hill, David E; Vidal, Marc

2006-01-01

The architecture and dynamics of molecular networks can provide an understanding of complex biological processes complementary to that obtained from the in-depth study of single genes and proteins. With a completely sequenced and well-annotated genome, a fully characterized cell lineage, and powerful tools available to dissect development, Caenorhabditis elegans, among metazoans, provides an optimal system to bridge cellular and organismal biology with the global properties of macromolecular networks. This chapter considers omic technologies available for C. elegans to describe molecular networks--encompassing transcriptional and phenotypic profiling as well as physical interaction mapping--and discusses how their individual and integrated applications are paving the way for a network-level understanding of C. elegans biology. PMID:18050437

PREFACE: Nanobiology: from physics and engineering to biology

NASA Astrophysics Data System (ADS)

Nussinov, Ruth; Alemán, Carlos

2006-03-01

Biological systems are inherently nano in scale. Unlike nanotechnology, nanobiology is characterized by the interplay between physics, materials science, synthetic organic chemistry, engineering and biology. Nanobiology is a new discipline, with the potential of revolutionizing medicine: it combines the tools, ideas and materials of nanoscience and biology; it addresses biological problems that can be studied and solved by nanotechnology; it devises ways to construct molecular devices using biomacromolecules; and it attempts to build molecular machines utilizing concepts seen in nature. Its ultimate aim is to be able to predictably manipulate these, tailoring them to specified needs. Nanobiology targets biological systems and uses biomacromolecules. Hence, on the one hand, nanobiology is seemingly constrained in its scope as compared to general nanotechnology. Yet the amazing intricacy of biological systems, their complexity, and the richness of the shapes and properties provided by the biological polymers, enrich nanobiology. Targeting biological systems entails comprehension of how they work and the ability to use their components in design. From the physical standpoint, ultimately, if we are to understand biology we need to learn how to apply physical principles to figure out how these systems actually work. The goal of nanobiology is to assist in probing these systems at the appropriate length scale, heralding a new era in the biological, physical and chemical sciences. Biology is increasingly asking quantitative questions. Quantitation is essential if we are to understand how the cell works, and the details of its regulation. The physical sciences provide tools and strategies to obtain accurate measurements and simulate the information to allow comprehension of the processes. Nanobiology is at the interface of the physical and the biological sciences. Biology offers to the physical sciences fascinating problems, sophisticated systems and a rich repertoire of shapes and materials. Inspection of the protein structure databank illustrates the breadth of scaffolds, shapes and properties that protein molecules and their building blocks can provide. Via a shape-guided self-assembly strategy, these can be put together toward a specific function. Further, by inserting synthetic non-natural residues at judiciously selected positions, or synthetic peptide linkers, we may selectively rigidify the construct, or obtain a totally new world of shapes and scaffolds. Such broadening of the chemical space may lead to an almost unlimited range of nanosystems and architectures. Merging computation with experiment will accelerate nanodesign. Computational modeling will enhance the application of nanotechnology to key areas such as drug delivery and biomaterial design. Nanobiology is a field where interdisciplinary collaborations are essential and disciplines converge. Discipline convergence should enable the quantitation, leading to a better understanding of the regulatory networks within cells and between cells of an organism. These networks dictate how a cell responds to external stimuli, which in turn activate signaling cascades. It should allow the addressing of a broad range of questions on the structure and function of the cytoskeleton; the nuclear envelope; signal transduction by membrane embedded receptors; the nanomechanical properties of the extracellular matrix; nuclear transport; and voltage induced channel gating. For successful nanostructure design, we need to figure out and be able to control the intermolecular associations. For a stable functional construct, there are two key elements: first, the conformations of the building blocks in the designed structure should follow their natural tendencies; and second, the associations should be favorable. Molecules interact through their surfaces. Thus, favorable associations derive from shape complementarity and contributions of the various physical components. Nanobiology is in its infancy. Yet, biology provides an enormous range of engaging and stimulating problems with many in vivo examples of intricate, complex, fascinating biological systems. Understanding, mimicking and controlling the devices which target these processes and which are constructed from these molecules is a tremendous challenge to the converging disciplines in nanobiology.

Genomes, Proteomes and the Central Dogma

PubMed Central

Franklin, Sarah; Vondriska, Thomas M.

2011-01-01

Systems biology, with its associated technologies of proteomics, genomics and metabolomics, is driving the evolution of our understanding of cardiovascular physiology. Rather than studying individual molecules or even single reactions, a systems approach allows integration of orthogonal datasets from distinct tiers of biological data, including gene, RNA, protein, metabolite and other component networks. Together these networks give rise to emergent properties of cellular function and it is their reprogramming that causes disease. We present five observations regarding how systems biology is guiding a revisiting of the central dogma: (i) de-emphasizing the unidirectional flow of information from genes to proteins; (ii) revealing the role of modules of molecules as opposed to individual proteins acting in isolation; (iii) enabling discovery of novel emergent properties; (iv) demonstrating the importance of networks in biology; and (v) adding new dimensionality to the study of biological systems. PMID:22010165

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

PubMed

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.

Exploring the MACH Model's Potential as a Metacognitive Tool to Help Undergraduate Students Monitor Their Explanations of Biological Mechanisms

ERIC Educational Resources Information Center

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

When undergraduate biology students learn to explain biological mechanisms, they face many challenges and may overestimate their understanding of living systems. Previously, we developed the MACH model of four components used by expert biologists to explain mechanisms: Methods, Analogies, Context, and How. This study explores the implementation of…

Radiation-Related Treatment Effects across the Age Spectrum: Differences and Similarities or What The Old and Young Can Learn From Each Other

PubMed Central

Krasin, Matthew J.; Constine, Louis S.; Friedman, Debra; Marks, Lawrence B.

2010-01-01

Radiation related effects in children and adults limit the delivery of effective radiation doses and result in long-term morbidity affecting function and quality of life. Improvements in our understanding of the etiology and biology of these effects, including the influence of clinical variables, dosimetric factors, and the underlying biologic processes has made treatment safer and more efficacious. However, the approach to studying and understanding these effects differs between children and adults. By using the pulmonary and skeletal organ systems as examples, comparisons are made across the age spectrum for radiation related effects including pneumonitis, pulmonary fibrosis, osteonecrosis and fracture. Methods for dosimetric analysis, incorporation of imaging and biology as well a length of follow-up are compared, contrasted and discussed for both organ systems in children and adults. Better understanding of each age specific approach and how it differs may improve our ability to study late effects of radiation across the ages PMID:19959028

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

PubMed

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

Predictive Models of Nanotoxicity: Relationship of Physicochemical Properties to Particle Movement Through Biological Barriers

EPA Science Inventory

Understanding the linkage between the physicochemical (PC) properties of nanoparticles (NP) and their activation of biological systems is poorly understood, yet fundamental to predicting nanotoxicity, idenitifying mode of actions and developing appropriate and effective regul...

Application of Mechanistic Toxicology Data to Ecological Risk Assessments

EPA Science Inventory

The ongoing evolution of knowledge and tools in the areas of molecular biology, bioinformatics, and systems biology holds significant promise for reducing uncertainties associated with ecological risk assessment. As our understanding of the mechanistic basis of responses of organ...

Potentials of single-cell biology in identification and validation of disease biomarkers.

PubMed

Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

2016-09-01

Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Consistent design schematics for biological systems: standardization of representation in biological engineering

PubMed Central

Matsuoka, Yukiko; Ghosh, Samik; Kitano, Hiroaki

2009-01-01

The discovery by design paradigm driving research in synthetic biology entails the engineering of de novo biological constructs with well-characterized input–output behaviours and interfaces. The construction of biological circuits requires iterative phases of design, simulation and assembly, leading to the fabrication of a biological device. In order to represent engineered models in a consistent visual format and further simulating them in silico, standardization of representation and model formalism is imperative. In this article, we review different efforts for standardization, particularly standards for graphical visualization and simulation/annotation schemata adopted in systems biology. We identify the importance of integrating the different standardization efforts and provide insights into potential avenues for developing a common framework for model visualization, simulation and sharing across various tools. We envision that such a synergistic approach would lead to the development of global, standardized schemata in biology, empowering deeper understanding of molecular mechanisms as well as engineering of novel biological systems. PMID:19493898

Synthetic biology: exploring and exploiting genetic modularity through the design of novel biological networks.

PubMed

Agapakis, Christina M; Silver, Pamela A

2009-07-01

Synthetic biology has been used to describe many biological endeavors over the past thirty years--from designing enzymes and in vitro systems, to manipulating existing metabolisms and gene expression, to creating entirely synthetic replicating life forms. What separates the current incarnation of synthetic biology from the recombinant DNA technology or metabolic engineering of the past is an emphasis on principles from engineering such as modularity, standardization, and rigorously predictive models. As such, synthetic biology represents a new paradigm for learning about and using biological molecules and data, with applications in basic science, biotechnology, and medicine. This review covers the canonical examples as well as some recent advances in synthetic biology in terms of what we know and what we can learn about the networks underlying biology, and how this endeavor may shape our understanding of living systems.

Big data mining powers fungal research: recent advances in fission yeast systems biology approaches.

PubMed

Wang, Zhe

2017-06-01

Biology research has entered into big data era. Systems biology approaches therefore become the powerful tools to obtain the whole landscape of how cell separate, grow, and resist the stresses. Fission yeast Schizosaccharomyces pombe is wonderful unicellular eukaryote model, especially studying its division and metabolism can facilitate to understanding the molecular mechanism of cancer and discovering anticancer agents. In this perspective, we discuss the recent advanced fission yeast systems biology tools, mainly focus on metabolomics profiling and metabolic modeling, protein-protein interactome and genetic interaction network, DNA sequencing and applications, and high-throughput phenotypic screening. We therefore hope this review can be useful for interested fungal researchers as well as bioformaticians.

Towards a minimal stochastic model for a large class of diffusion-reactions on biological membranes.

PubMed

Chevalier, Michael W; El-Samad, Hana

2012-08-28

Diffusion of biological molecules on 2D biological membranes can play an important role in the behavior of stochastic biochemical reaction systems. Yet, we still lack a fundamental understanding of circumstances where explicit accounting of the diffusion and spatial coordinates of molecules is necessary. In this work, we illustrate how time-dependent, non-exponential reaction probabilities naturally arise when explicitly accounting for the diffusion of molecules. We use the analytical expression of these probabilities to derive a novel algorithm which, while ignoring the exact position of the molecules, can still accurately capture diffusion effects. We investigate the regions of validity of the algorithm and show that for most parameter regimes, it constitutes an accurate framework for studying these systems. We also document scenarios where large spatial fluctuation effects mandate explicit consideration of all the molecules and their positions. Taken together, our results derive a fundamental understanding of the role of diffusion and spatial fluctuations in these systems. Simultaneously, they provide a general computational methodology for analyzing a broad class of biological networks whose behavior is influenced by diffusion on membranes.

A Systems Biology Approach to Iron Metabolism

PubMed Central

Chifman, J.; Laubenbacher, R.; Torti, S.V.

2015-01-01

Iron is critical to the survival of almost all living organisms. However, inappropriately low or high levels of iron are detrimental and contribute to a wide range of diseases. Recent advances in the study of iron metabolism have revealed multiple intricate pathways that are essential to the maintenance of iron homeostasis. Further, iron regulation involves processes at several scales, ranging from the subcellular to the organismal. This complexity makes a systems biology approach crucial, with its enabling technology of computational models based on a mathematical description of regulatory systems. Systems biology may represent a new strategy for understanding imbalances in iron metabolism and their underlying causes. PMID:25480643

The rise of the starlet sea anemone Nematostella vectensis as a model system to investigate development and regeneration

PubMed Central

Rentzsch, Fabian; Röttinger, Eric

2016-01-01

Reverse genetics and next‐generation sequencing unlocked a new era in biology. It is now possible to identify an animal(s) with the unique biology most relevant to a particular question and rapidly generate tools to functionally dissect that biology. This review highlights the rise of one such novel model system, the starlet sea anemone Nematostella vectensis. Nematostella is a cnidarian (corals, jellyfish, hydras, sea anemones, etc.) animal that was originally targeted by EvoDevo researchers looking to identify a cnidarian animal to which the development of bilaterians (insects, worms, echinoderms, vertebrates, mollusks, etc.) could be compared. Studies in Nematostella have accomplished this goal and informed our understanding of the evolution of key bilaterian features. However, Nematostella is now going beyond its intended utility with potential as a model to better understand other areas such as regenerative biology, EcoDevo, or stress response. This review intends to highlight key EvoDevo insights from Nematostella that guide our understanding about the evolution of axial patterning mechanisms, mesoderm, and nervous systems in bilaterians, as well as to discuss briefly the potential of Nematostella as a model to better understand the relationship between development and regeneration. Lastly, the sum of research to date in Nematostella has generated a variety of tools that aided the rise of Nematostella to a viable model system. We provide a catalogue of current resources and techniques available to facilitate investigators interested in incorporating Nematostella into their research. WIREs Dev Biol 2016, 5:408–428. doi: 10.1002/wdev.222 For further resources related to this article, please visit the WIREs website. PMID:26894563

The "What Is a System" Reflection Interview as a Knowledge Integration Activity for High School Students' Understanding of Complex Systems in Human Biology

ERIC Educational Resources Information Center

Tripto, Jaklin; Ben-Zvi Assaraf, Orit; Snapir, Zohar; Amit, Miriam

2016-01-01

This study examined the reflection interview as a tool for assessing and facilitating the use of "systems language" amongst 11th grade students who have recently completed their first year of high school biology. Eighty-three students composed two concept maps in the 10th grade--one at the beginning of the school year and one at its end.…

Systems biology of cellular membranes: a convergence with biophysics.

PubMed

Chabanon, Morgan; Stachowiak, Jeanne C; Rangamani, Padmini

2017-09-01

Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

Top-down models in biology: explanation and control of complex living systems above the molecular level.

PubMed

Pezzulo, Giovanni; Levin, Michael

2016-11-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. © 2016 The Author(s).

Top-down models in biology: explanation and control of complex living systems above the molecular level

PubMed Central

2016-01-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. PMID:27807271

Using a Virtual Tissue Culture System to Assist Students in Understanding Life at the Cellular Level

ERIC Educational Resources Information Center

McLauglin, Jacqueline S.; Seaquist, Stephen B.

2008-01-01

In every biology course ever taught in the nation's classrooms, and in every biology book ever published, students are taught about the "cell." The cell is as fundamental to biology as the atom is to chemistry. Truly, everything an organism does occurs fundamentally at the cellular level. Beyond memorizing the cellular definition, students are not…

Life into Space: Space Life Sciences Experiments, Ames Research Center, Kennedy Space Center, 1991-1998, Including Profiles of 1996-1998 Experiments

NASA Technical Reports Server (NTRS)

Souza, Kenneth (Editor); Etheridge, Guy (Editor); Callahan, Paul X. (Editor)

2000-01-01

We have now conducted space life sciences research for more than four decades. The continuing interest in studying the way living systems function in space derives from two main benefits of that research. First, in order for humans to engage in long-term space travel, we must understand and develop measures to counteract the most detrimental effects of space flight on biological systems. Problems in returning to the conditions of Earth must be kept to a manageable level. Second, increasing our understanding of how organisms function in the absence of gravity gives us new understanding of fundamental biological processes. This information can be used to improve human health and the quality of life on Earth.

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

PubMed Central

Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

Integrating Omics Technologies to Study Pulmonary Physiology and Pathology at the Systems Level

PubMed Central

Pathak, Ravi Ramesh; Davé, Vrushank

2014-01-01

Assimilation and integration of “omics” technologies, including genomics, epigenomics, proteomics, and metabolomics has readily altered the landscape of medical research in the last decade. The vast and complex nature of omics data can only be interpreted by linking molecular information at the organismic level, forming the foundation of systems biology. Research in pulmonary biology/medicine has necessitated integration of omics, network, systems and computational biology data to differentially diagnose, interpret, and prognosticate pulmonary diseases, facilitating improvement in therapy and treatment modalities. This review describes how to leverage this emerging technology in understanding pulmonary diseases at the systems level –called a “systomic” approach. Considering the operational wholeness of cellular and organ systems, diseased genome, proteome, and the metabolome needs to be conceptualized at the systems level to understand disease pathogenesis and progression. Currently available omics technology and resources require a certain degree of training and proficiency in addition to dedicated hardware and applications, making them relatively less user friendly for the pulmonary biologist and clinicians. Herein, we discuss the various strategies, computational tools and approaches required to study pulmonary diseases at the systems level for biomedical scientists and clinical researchers. PMID:24802001

Toward a systems-level analysis of infection biology: a new method for conducting genetic screens in human cells.

PubMed

Stanley, Sarah A; Hung, Deborah T

2009-12-16

Loss-of-function genetic screens have facilitated great strides in our understanding of the biology of model organisms but have not been possible in diploid human cells. A recent report by Brummelkamp's group in Science describes the use of insertional mutagenesis to generate loss-of-function alleles in a largely haploid human cell line and demonstrates the versatility of this method in screens designed to investigate the host/pathogen interaction. This approach has strengths that are complementary to existing strategies and will facilitate progress toward a systems-level understanding of infectious disease and ultimately the development of new therapeutics.

Biokinetics of zinc oxide nanoparticles: toxicokinetics, biological fates, and protein interaction

PubMed Central

Choi, Soo-Jin; Choy, Jin-Ho

2014-01-01

Biokinetic studies of zinc oxide (ZnO) nanoparticles involve systematic and quantitative analyses of absorption, distribution, metabolism, and excretion in plasma and tissues of whole animals after exposure. A full understanding of the biokinetics provides basic information about nanoparticle entry into systemic circulation, target organs of accumulation and toxicity, and elimination time, which is important for predicting the long-term toxic potential of nanoparticles. Biokinetic behaviors can be dependent on physicochemical properties, dissolution property in biological fluids, and nanoparticle–protein interaction. Moreover, the determination of biological fates of ZnO nanoparticles in the systemic circulation and tissues is critical in interpreting biokinetic behaviors and predicting toxicity potential as well as mechanism. This review focuses on physicochemical factors affecting the biokinetics of ZnO nanoparticles, in concert with understanding bioavailable fates and their interaction with proteins. PMID:25565844

Use of EPR to Solve Biochemical Problems

PubMed Central

Sahu, Indra D.; McCarrick, Robert M.; Lorigan, Gary A.

2013-01-01

EPR spectroscopy is a very powerful biophysical tool that can provide valuable structural and dynamic information on a wide variety of biological systems. The intent of this review is to provide a general overview for biochemists and biological researchers on the most commonly used EPR methods and how these techniques can be used to answer important biological questions. The topics discussed could easily fill one or more textbooks; thus, we present a brief background on several important biological EPR techniques and an overview of several interesting studies that have successfully used EPR to solve pertinent biological problems. The review consists of the following sections: an introduction to EPR techniques, spin labeling methods, and studies of naturally occurring organic radicals and EPR active transition metal systems which are presented as a series of case studies in which EPR spectroscopy has been used to greatly further our understanding of several important biological systems. PMID:23961941

Use of Primary Human Cell Systems for Creating Predictive Toxicology Profiles

EPA Science Inventory

Use of cellular regulatory networks to detect and distinguish effects of compounds with a broad range of on- and off-target mechanisms and biological processes provides an opportunity to understand toxicity mechanisms of action. Here we use the Biologically Multiplexed Activity P...

APPLICATION OF GENOMIC AND PROTEOMIC INDICATORS TO CHARACTERIZE EXPOSURE OF AQUATIC ORGANISMS TO ENVIRONMENTAL CONTAMINANTS

EPA Science Inventory

Advances in molecular biological methods are continually being brought to bear on human health research, from a basic understanding of systems biology to identification of toxicity pathways for environmental stressors and to correlations of molecular indicators with physiological...

Yeast: An Experimental Organism for Modern Biology.

ERIC Educational Resources Information Center

Botstein, David; Fink, Gerald R.

1988-01-01

Discusses the applicability and advantages of using yeasts as popular and ideal model systems for studying and understanding eukaryotic biology at the cellular and molecular levels. Cites experimental tractability and the cooperative tradition of the research community of yeast biologists as reasons for this success. (RT)

Genome Editing to Study Ca2+ Homeostasis in Zebrafish Cone Photoreceptors.

PubMed

Brockerhoff, Susan E

2017-01-01

Photoreceptors are specialized sensory neurons with unique biological features. Phototransduction is well understood due in part to the exclusive expression and function of the molecular components of this cascade. Many other processes are less well understood, but also extremely important for understanding photoreceptor function and for treating disease. One example is the role of Ca 2+ in the cell body and overall compartmentalization and regulation of Ca 2+ within the cell. The recent development of CRISPR/Cas9 genome editing techniques has made it possible to rapidly and cheaply alter specific genes. This will help to define the biological function of elusive processes that have been more challenging to study. CRISPR/Cas9 has been optimized in many systems including zebrafish, which already has some distinct advantages for studying photoreceptor biology and function. These new genome editing technologies and the continued use of the zebrafish model system will help advance our understanding of important understudied aspects of photoreceptor biology.

Thiosulfoxide (Sulfane) Sulfur: New Chemistry and New Regulatory Roles in Biology

PubMed Central

Toohey, John I.; Cooper, Arthur J. L.

2014-01-01

The understanding of sulfur bonding is undergoing change. Old theories on hypervalency of sulfur and the nature of the chalcogen-chalcogen bond are now questioned. At the same time, there is a rapidly expanding literature on the effects of sulfur in regulating biological systems. The two fields are inter-related because the new understanding of the thiosulfoxide bond helps to explain the newfound roles of sulfur in biology. This review examines the nature of thiosulfoxide (sulfane, S0) sulfur, the history of its regulatory role, its generation in biological systems, and its functions in cells. The functions include synthesis of cofactors (molybdenum cofactor, iron-sulfur clusters), sulfuration of tRNA, modulation of enzyme activities, and regulating the redox environment by several mechanisms (including the enhancement of the reductive capacity of glutathione). A brief review of the analogous form of selenium suggests that the toxicity of selenium may be due to over-reduction caused by the powerful reductive activity of glutathione perselenide. PMID:25153879

Emerging concepts for management of river ecosystems and challenges to applied integration of physical and biological sciences in the Pacific Northwest, USA

Treesearch

Bruce E. Rieman; Jason B. Dunham; James L. Clayton

2006-01-01

Integration of biological and physical concepts is necessary to understand and conserve the ecological integrity of river systems. Past attempts at integration have often focused at relatively small scales and on mechanistic models that may not capture the complexity of natural systems leaving substantial uncertainty about ecological responses to management actions....

Farm to Table and beyond: Helping Students Make Sense of the Global Food System

ERIC Educational Resources Information Center

Koch, Pamela; Barton, Angela Calabrese; Contento, Isobel; Crabtree, Margo

2008-01-01

It is not enough for students to acquire knowledge about how food is produced and processed; they must also come to understand the biological and environmental contexts in which food production, processing, and transportation take place. Through diagramming, students begin to understand that our food system has a series of interacting parts and…

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.

PubMed

Arakawa, Kazuharu; Yamada, Yohei; Shinoda, Kosaku; Nakayama, Yoichi; Tomita, Masaru

2006-03-23

Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments.

PubMed

Kudoh, Hiroshi

2016-04-01

Phenology refers to the study of seasonal schedules of organisms. Molecular phenology is defined here as the study of the seasonal patterns of organisms captured by molecular biology techniques. The history of molecular phenology is reviewed briefly in relation to advances in the quantification technology of gene expression. High-resolution molecular phenology (HMP) data have enabled us to study phenology with an approach of in natura systems biology. I review recent analyses of FLOWERING LOCUS C (FLC), a temperature-responsive repressor of flowering, along the six steps in the typical flow of in natura systems biology. The extensive studies of the regulation of FLC have made this example a successful case in which a comprehensive understanding of gene functions has been progressing. The FLC-mediated long-term memory of past temperatures creates time lags with other seasonal signals, such as photoperiod and short-term temperature. Major signals that control flowering time have a phase lag between them under natural conditions, and hypothetical phase lag calendars are proposed as mechanisms of season detection in plants. Transcriptomic HMP brings a novel strategy to the study of molecular phenology, because it provides a comprehensive representation of plant functions. I discuss future perspectives of molecular phenology from the standpoints of molecular biology, evolutionary biology and ecology. © 2015 The Author. New Phytologist © 2015 New Phytologist Trust.

Autism genetics: searching for specificity and convergence

PubMed Central

2012-01-01

Advances in genetics and genomics have improved our understanding of autism spectrum disorders. As many genes have been implicated, we look to points of convergence among these genes across biological systems to better understand and treat these disorders. PMID:22849751

Implementation Plans for a Systems Microbiology and Extremophile Research Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiley, H. S.

Introduction Biological organisms long ago solved many problems for which scientists and engineers seek solutions. Microbes in particular offer an astonishingly diverse set of capabilities that can help revolutionize our approach to solving many important DOE problems. For example, photosynthetic organisms can generate hydrogen from light while simultaneously sequestering carbon. Others can produce enzymes that break down cellulose and other biomass to produce liquid fuels. Microbes in water and soil can capture carbon and store it in the earth and ocean depths. Understanding the dynamic interaction between living organisms and the environment is critical to predicting and mitigating the impactsmore » of energy-production-related activities on the environment and human health. Collectively, microorganisms contain most of the biochemical diversity on Earth and they comprise nearly one-half of its biomass. They primary impact the planet by acting as catalysts of biogeochemical cycles; they capture light energy and fix CO2 in the worlds oceans, they degrade plant polymers and convert them to humus in soils, they weather rocks and facilitate mineral precipitation. Although the ability of selected microorganisms to participate in these processes is known, they rarely live in monoculture but rather function within communities. In spite of this, little is known about the composition of microbial communities and how individual species function within them. We lack an understanding of the nature of the individual organisms and their genes, how they interact to perform complex functions such as energy and materials exchange, how they sense and respond to their environment and how they evolve and adapt to environmental change. Understanding these aspects of microbes and their communities would be transformational with far-reaching impacts on climate, energy and human health. This knowledge would create a foundation for predicting their behavior and, ultimately, manipulating them to solve DOE problems. Recent advances in whole-genome sequencing for a variety of organisms and improvements in high-throughput instrumentation have contributed to a rapid transition of the biological research paradigm towards understanding biology at a systems level. As a result, biology is evolving from a descriptive to a quantitative, ultimately predictive science where the ability to collect and productively use large amounts of biological data is crucial. Understanding how the ensemble of proteins in cells gives rise to biological outcomes is fundamental to systems biology. These advances will require new technologies and approaches to measure and track the temporal and spatial disposition of proteins in cells and how networks of proteins and other regulatory molecules give rise to specific activities. The DOE has a strong interest in promoting the application of systems biology to understanding microbial function and this comprises a major focus of its Genomics:GTL program. A major problem in pursuing what has been termed “systems microbiology” is the lack of the facilities and infrastructure for conducting this new style of research. To solve this problem, the Genomics:GTL program has funded a number of large-scale research centers focused on either mission-oriented outcomes, such as bioenergy, or basic technologies, such as gene sequencing, high-throughput proteomics or the identification of protein complexes. Although these centers generate data that will be useful to the research community, their scientific goals are relatively narrow and are not designed to accommodate the general community need for advanced capabilities for systems microbiology research.« less

The necessity of a theory of biology for tissue engineering: metabolism-repair systems.

PubMed

Ganguli, Suman; Hunt, C Anthony

2004-01-01

Since there is no widely accepted global theory of biology, tissue engineering and bioengineering lack a theoretical understanding of the systems being engineered. By default, tissue engineering operates with a "reductionist" theoretical approach, inherited from traditional engineering of non-living materials. Long term, that approach is inadequate, since it ignores essential aspects of biology. Metabolism-repair systems are a theoretical framework which explicitly represents two "functional" aspects of living organisms: self-repair and self-replication. Since repair and replication are central to tissue engineering, we advance metabolism-repair systems as a potential theoretical framework for tissue engineering. We present an overview of the framework, and indicate directions to pursue for extending it to the context of tissue engineering. We focus on biological networks, both metabolic and cellular, as one such direction. The construction of these networks, in turn, depends on biological protocols. Together these concepts may help point the way to a global theory of biology appropriate for tissue engineering.

How do biological systems discriminate among physically similar ions?

PubMed

Diamond, J M

1975-10-01

This paper reviews the history of understanding how biological systems can discriminate so strikingly among physically similar ions, especially alkali cations. Appreciation of qualitative regularities ("permitted sequences") and quantitative regularities ("selectivity isotherms") in ion selectivity grew first from studies of ion exchangers and glass electrodes, then of biological systems such as enzymes and cell membranes, and most recently of lipid bilayers doped with model pores and carriers. Discrimination of ions depends on both electrostatic and steric forces. "Black-box" studies on intact biological membranes have in some cases yielded molecular clues to the structure of the actual biological pores and carriers. Major current problems involve the extraction of these molecules; how to do it, what to do when it is achieved, and how (and if) it is relevant to the central problems of membrane function. Further advances are expected soon from studies of rate barriers within membranes, of voltage-dependent ("excitable") conducting channels, and of increasingly complex model systems and biological membranes.

Omics/systems biology and cancer cachexia.

PubMed

Gallagher, Iain J; Jacobi, Carsten; Tardif, Nicolas; Rooyackers, Olav; Fearon, Kenneth

2016-06-01

Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia. Copyright © 2016. Published by Elsevier Ltd.

Building biological foundries for next-generation synthetic biology.

PubMed

Chao, Ran; Yuan, YongBo; Zhao, HuiMin

2015-07-01

Synthetic biology is an interdisciplinary field that takes top-down approaches to understand and engineer biological systems through design-build-test cycles. A number of advances in this relatively young field have greatly accelerated such engineering cycles. Specifically, various innovative tools were developed for in silico biosystems design, DNA de novo synthesis and assembly, construct verification, as well as metabolite analysis, which have laid a solid foundation for building biological foundries for rapid prototyping of improved or novel biosystems. This review summarizes the state-of-the-art technologies for synthetic biology and discusses the challenges to establish such biological foundries.

Systems biology of seeds: deciphering the molecular mechanisms of seed storage, dormancy and onset of germination.

PubMed

Sreenivasulu, Nese

2017-05-01

Seeds are heterogeneous storage reserves with wide array of storage compounds that include various soluble carbohydrates, starch polymer, storage proteins and lipids. These stored reserves comprise 70% of the world's caloric intake in the form of food and animal feed produced through sustainable agriculture, which contributes to food and nutritional security. Seed systems biology remains an enigmatic subject in understanding seed storage processes, maturation and pre-germinative metabolism. The reviews and research articles covered in this special issue of Plant Cell Reports highlight recent advances made in the area of seed biology that cover various systems biology applications such as gene regulatory networks, metabolomics, epigenetics and the role of micro-RNA in seed development.

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zabaras, Nicolas J.

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

Are attractors 'strange', or is life more complicated than the simple laws of physics?

PubMed

Pogun, S

2001-01-01

Interesting and intriguing questions involve complex systems whose properties cannot be explained fully by reductionist approaches. Last century was dominated by physics, and applying the simple laws of physics to biology appeared to be a practical solution to understand living organisms. However, although some attributes of living organisms involve physico-chemical properties, the genetic program and evolutionary history of complex biological systems make them unique and unpredictable. Furthermore, there are and will be 'unobservable' phenomena in biology which have to be accounted for.

Oligodendroglia: metabolic supporters of axons.

PubMed

Morrison, Brett M; Lee, Youngjin; Rothstein, Jeffrey D

2013-12-01

Axons are specialized extensions of neurons that are critical for the organization of the nervous system. To maintain function in axons that often extend some distance from the cell body, specialized mechanisms of energy delivery are likely to be necessary. Over the past decade, greater understanding of human demyelinating diseases and the development of animal models have suggested that oligodendroglia are critical for maintaining the function of axons. In this review, we discuss evidence for the vulnerability of neurons to energy deprivation, the importance of oligodendrocytes for axon function and survival, and recent data suggesting that transfer of energy metabolites from oligodendroglia to axons through monocarboxylate transporter 1 (MCT1) may be critical for the survival of axons. This pathway has important implications both for the basic biology of the nervous system and for human neurological disease. New insights into the role of oligodendroglial biology provide an exciting opportunity for revisions in nervous system biology, understanding myelin-based disorders, and therapeutics development. Copyright © 2013 Elsevier Ltd. All rights reserved.

Games network and application to PAs system.

PubMed

Chettaoui, C; Delaplace, F; Manceny, M; Malo, M

2007-02-01

In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.

Reaching for Excellence.

ERIC Educational Resources Information Center

Wright, Emmett L.; Perna, Jack A.

1992-01-01

Presents the four program goals for biology set forth in the National Science Teacher Association's "A Focus on Excellence: Biology Revisited" to (1) address biosphere, human society, and individual needs; (2) encourage students to experience, understand, and appreciate of natural systems; (3) apply the basic concept of the biosphere; and (4)…

Proof of Concept: A review on how network and systems biology approaches aid in the discovery of potent anticancer drug combinations

PubMed Central

Azmi, Asfar S.; Wang, Zhiwei; Philip, Philip A.; Mohammad, Ramzi M.; Sarkar, Fazlul H.

2010-01-01

Cancer therapies that target key molecules have not fulfilled expected promises for most common malignancies. Major challenges include the incomplete understanding and validation of these targets in patients, the multiplicity and complexity of genetic and epigenetic changes in the majority of cancers, and the redundancies and cross-talk found in key signaling pathways. Collectively, the uses of single-pathway targeted approaches are not effective therapies for human malignances. To overcome these barriers, it is important to understand the molecular cross-talk among key signaling pathways and how they may be altered by targeted agents. This requires innovative approaches such as understanding the global physiological environment of target proteins and the effects of modifying them without losing key molecular details. Such strategies will aid the design of novel therapeutics and their combinations against multifaceted diseases where efficacious combination therapies will focus on altering multiple pathways rather than single proteins. Integrated network modeling and systems biology has emerged as a powerful tool benefiting our understanding of drug mechanism of action in real time. This mini-review highlights the significance of the network and systems biology-based strategy and presents a “proof-of-concept” recently validated in our laboratory using the example of a combination treatment of oxaliplatin and the MDM2 inhibitor MI-219 in genetically complex and incurable pancreatic adenocarcinoma. PMID:21041384

Dynamics of problem setting and framing in citizen discussions on synthetic biology

PubMed Central

Betten, Afke Wieke; Broerse, Jacqueline E.W.; Kupper, Frank

2017-01-01

Synthetic biology is an emerging scientific field where engineers and biologists design and build biological systems for various applications. Developing synthetic biology responsibly in the public interest necessitates a meaningful societal dialogue. In this article, we argue that facilitating such a dialogue requires an understanding of how people make sense of synthetic biology. We performed qualitative research to unravel the underlying dynamics of problem setting and framing in citizen discussions on synthetic biology. We found that most people are not inherently for or against synthetic biology as a technology or development in itself, but that their perspectives are framed by core values about our relationships with science and technology and that sensemaking is much dependent on the context and general feelings of (dis)content. Given that there are many assumptions focused on a more binary idea of the public’s view, we emphasize the need for frame awareness and understanding in a meaningful dialogue. PMID:28597721

A Theoretical Mechanism of Szilard Engine Function in Nucleic Acids and the Implications for Quantum Coherence in Biological Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthew Mihelic, F.

2010-12-22

Nucleic acids theoretically possess a Szilard engine function that can convert the energy associated with the Shannon entropy of molecules for which they have coded recognition, into the useful work of geometric reconfiguration of the nucleic acid molecule. This function is logically reversible because its mechanism is literally and physically constructed out of the information necessary to reduce the Shannon entropy of such molecules, which means that this information exists on both sides of the theoretical engine, and because information is retained in the geometric degrees of freedom of the nucleic acid molecule, a quantum gate is formed through whichmore » multi-state nucleic acid qubits can interact. Entangled biophotons emitted as a consequence of symmetry breaking nucleic acid Szilard engine (NASE) function can be used to coordinate relative positioning of different nucleic acid locations, both within and between cells, thus providing the potential for quantum coherence of an entire biological system. Theoretical implications of understanding biological systems as such 'quantum adaptive systems' include the potential for multi-agent based quantum computing, and a better understanding of systemic pathologies such as cancer, as being related to a loss of systemic quantum coherence.« less

A Theoretical Mechanism of Szilard Engine Function in Nucleic Acids and the Implications for Quantum Coherence in Biological Systems

NASA Astrophysics Data System (ADS)

Matthew Mihelic, F.

2010-12-01

Nucleic acids theoretically possess a Szilard engine function that can convert the energy associated with the Shannon entropy of molecules for which they have coded recognition, into the useful work of geometric reconfiguration of the nucleic acid molecule. This function is logically reversible because its mechanism is literally and physically constructed out of the information necessary to reduce the Shannon entropy of such molecules, which means that this information exists on both sides of the theoretical engine, and because information is retained in the geometric degrees of freedom of the nucleic acid molecule, a quantum gate is formed through which multi-state nucleic acid qubits can interact. Entangled biophotons emitted as a consequence of symmetry breaking nucleic acid Szilard engine (NASE) function can be used to coordinate relative positioning of different nucleic acid locations, both within and between cells, thus providing the potential for quantum coherence of an entire biological system. Theoretical implications of understanding biological systems as such "quantum adaptive systems" include the potential for multi-agent based quantum computing, and a better understanding of systemic pathologies such as cancer, as being related to a loss of systemic quantum coherence.

Conceptual understandings of biology in pre-service science educators and undergraduate biology students at Colorado institutions of higher education

NASA Astrophysics Data System (ADS)

Smith, Trenton John

Pre-service secondary science individuals, future middle or high school instructors training to become teachers, along with both Honors and general first year undergraduate biology students were investigated to determine how they reason about and understand two core topics in Biology: matter and energy flow through biological systems and evolution by natural selection. Diagnostic Question Clusters were used to assess student understanding of the processes by which matter and energy flow through biological systems over spatial scales, from the atomic-molecular to ecosystem levels. Key concepts and identified misconceptions were examined over topics of evolution by natural selection using the multiple-choice Concept Inventory of Natural Selection (CINS) and open-response Assessing COntextual Reasoning about Natural Selection (ACORNS). Pre-service teachers used more scientifically based reasoning than the undergraduate students over the topics of matter and energy flow. The Honors students used more scientific and less improper informal reasoning than the general undergraduates over matter and energy flow. Honors students performed best on both the CINS and ACORNS items over natural selection, while the general undergraduates scored the lowest on the CINS, and the pre-service instructors scored lowest on the ACORNS. Overall, there remain a large proportion of students not consistently using scientific reasoning about these two important concepts, even in future secondary science teachers. My findings are similar to those of other published studies using the same assessments. In general, very few biology students at the college level use scientific reasoning that exhibits deep conceptual understanding. A reason for this could be that instructors fail to recognize deficiencies in student reasoning; they assume their students use principle-based reasoning. Another reason could be that principle-based reasoning is very difficult and our teaching approaches in college promote memorization of content rather than conceptual change. My findings are significant to the work and progression of concept inventories in biology education, as well as to the instructors of students at all levels of biology curriculum, and those of future science teachers.

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

The Comet Cometh: Evolving Developmental Systems.

PubMed

Jaeger, Johannes; Laubichler, Manfred; Callebaut, Werner

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule's prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach-which is based on reverse engineering, simulation, and mathematical analysis-the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

A molecular signaling approach to linking intraspecific variation and macro-evolutionary patterns.

PubMed

Swanson, Eli M; Snell-Rood, Emilie C

2014-11-01

Macro-evolutionary comparisons are a valued tool in evolutionary biology. Nevertheless, our understanding of how systems involved in molecular signaling change in concert with phenotypic diversification has lagged. We argue that integrating our understanding of the evolution of molecular signaling systems with phylogenetic comparative methods is an important step toward understanding the processes linking variation among individuals with variation among species. Focusing mostly on the endocrine system, we discuss how the complexity and mechanistic nature of molecular signaling systems may influence the application and interpretation of macro-evolutionary comparisons. We also detail five hypotheses concerning the role that physiological mechanisms can play in shaping macro-evolutionary patterns, and discuss ways in which these hypotheses could influence phenotypic diversification. Finally, we review a series of tools able to analyze the complexity of physiological systems and the way they change in concert with the phenotypes for which they coordinate development. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Is synthetic biology mechanical biology?

PubMed

Holm, Sune

2015-12-01

A widespread and influential characterization of synthetic biology emphasizes that synthetic biology is the application of engineering principles to living systems. Furthermore, there is a strong tendency to express the engineering approach to organisms in terms of what seems to be an ontological claim: organisms are machines. In the paper I investigate the ontological and heuristic significance of the machine analogy in synthetic biology. I argue that the use of the machine analogy and the aim of producing rationally designed organisms does not necessarily imply a commitment to mechanical biology. The ideal of applying engineering principles to biology is best understood as expressing recognition of the machine-unlikeness of natural organisms and the limits of human cognition. The paper suggests an interpretation of the identification of organisms with machines in synthetic biology according to which it expresses a strategy for representing, understanding, and constructing living systems that are more machine-like than natural organisms.

The Metals in the Biological Periodic System of the Elements: Concepts and Conjectures

PubMed Central

Maret, Wolfgang

2016-01-01

A significant number of chemical elements are either essential for life with known functions, or present in organisms with poorly defined functional outcomes. We do not know all the essential elements with certainty and we know even less about the functions of apparently non-essential elements. In this article, I discuss a basis for a biological periodic system of the elements and that biochemistry should include the elements that are traditionally part of inorganic chemistry and not only those that are in the purview of organic chemistry. A biological periodic system of the elements needs to specify what “essential” means and to which biological species it refers. It represents a snapshot of our present knowledge and is expected to undergo further modifications in the future. An integrated approach of biometal sciences called metallomics is required to understand the interactions of metal ions, the biological functions that their chemical structures acquire in the biological system, and how their usage is fine-tuned in biological species and in populations of species with genetic variations (the variome). PMID:26742035

Exploring the MACH Model’s Potential as a Metacognitive Tool to Help Undergraduate Students Monitor Their Explanations of Biological Mechanisms

PubMed Central

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

When undergraduate biology students learn to explain biological mechanisms, they face many challenges and may overestimate their understanding of living systems. Previously, we developed the MACH model of four components used by expert biologists to explain mechanisms: Methods, Analogies, Context, and How. This study explores the implementation of the model in an undergraduate biology classroom as an educational tool to address some of the known challenges. To find out how well students’ written explanations represent components of the MACH model before and after they were taught about it and why students think the MACH model was useful, we conducted an exploratory multiple case study with four interview participants. We characterize how two students explained biological mechanisms before and after a teaching intervention that used the MACH components. Inductive analysis of written explanations and interviews showed that MACH acted as an effective metacognitive tool for all four students by helping them to monitor their understanding, communicate explanations, and identify explanatory gaps. Further research, though, is needed to more fully substantiate the general usefulness of MACH for promoting students’ metacognition about their understanding of biological mechanisms. PMID:27252295

A Systems Approach to Exposure Modeling (ExpoCast)(FutureTox3)

EPA Science Inventory

Systems Biology might be described as the understanding of how interactions on multiple scales integrate into a homeostatic system. Systems Toxicology could then be the study of the impact of chemical perturbations of homeostasis. Systems exposure might then be the study of the i...

Student Teachers' Ways of Thinking and Ways of Understanding Digestion and the Digestive System in Biology

ERIC Educational Resources Information Center

Çimer, Sabiha Odabasi; Ursavas, Nazihan

2012-01-01

The purpose of this study was to identify the ways in which student teachers understand digestion and the digestive system and, subsequently, their ways of thinking, as reflected in their problem solving approaches and the justification schemes that they used to validate their claims. For this purpose, clinical interviews were conducted with 10…

Oceans of opportunity: exploring vertebrate hematopoiesis in zebrafish.

PubMed

Carroll, Kelli J; North, Trista E

2014-08-01

Exploitation of the zebrafish model in hematology research has surged in recent years, becoming one of the most useful and tractable systems for understanding regulation of hematopoietic development, homeostasis, and malignancy. Despite the evolutionary distance between zebrafish and humans, remarkable genetic and phenotypic conservation in the hematopoietic system has enabled significant advancements in our understanding of blood stem and progenitor cell biology. The strengths of zebrafish in hematology research lie in the ability to perform real-time in vivo observations of hematopoietic stem, progenitor, and effector cell emergence, expansion, and function, as well as the ease with which novel genetic and chemical modifiers of specific hematopoietic processes or cell types can be identified and characterized. Further, myriad transgenic lines have been developed including fluorescent reporter systems to aid in the visualization and quantification of specified cell types of interest and cell-lineage relationships, as well as effector lines that can be used to implement a wide range of experimental manipulations. As our understanding of the complex nature of blood stem and progenitor cell biology during development, in response to infection or injury, or in the setting of hematologic malignancy continues to deepen, zebrafish will remain essential for exploring the spatiotemporal organization and integration of these fundamental processes, as well as the identification of efficacious small molecule modifiers of hematopoietic activity. In this review, we discuss the biology of the zebrafish hematopoietic system, including similarities and differences from mammals, and highlight important tools currently utilized in zebrafish embryos and adults to enhance our understanding of vertebrate hematology, with emphasis on findings that have impacted our understanding of the onset or treatment of human hematologic disorders and disease. Copyright © 2014 ISEH - International Society for Experimental Hematology. Published by Elsevier Inc. All rights reserved.

Oceans of Opportunity: Exploring Vertebrate Hematopoiesis in Zebrafish

PubMed Central

Carroll, Kelli J.; North, Trista E.

2015-01-01

Exploitation of the zebrafish model in hematology research has surged in recent years, becoming one of the most useful and tractable systems for understanding regulation of hematopoietic development, homeostasis, and malignancy. Despite the evolutionary distance between zebrafish and humans, remarkable genetic and phenotypic conservation in the hematopoietic system has enabled significant advancements in our understanding of blood stem and progenitor cell (HSPC) biology. The strengths of zebrafish in hematology research lie in the ability to perform real-time in vivo observations of hematopoietic stem, progenitor and effector cell emergence, expansion and function, as well as the ease with which novel genetic and chemical modifiers of specific hematopoietic processes or cell-types can be identified and characterized. Further, a myriad of transgenic lines have been developed including fluorescent reporter systems to aid in the visualization and quantification of specified cell types of interest and cell-lineage relationships, as well as effector lines that can be used to implement a wide range of experimental manipulations. As our understanding of the complex nature of HSPC biology during development, in response to infection or injury, or in the setting of hematological malignancy, continues to deepen, zebrafish will remain essential for exploring the spatio-temporal organization and integration of these fundamental processes, as well as the identification of efficacious small molecule modifiers of hematopoietic activity. In this review, we discuss the biology of the zebrafish hematopoietic system, including similarities and differences from mammals, and highlight important tools currently utilized in zebrafish embryos and adults to enhance our understanding of vertebrate hematology, with emphasis on findings that have impacted our understanding of the onset or treatment of human hematologic disorders and disease. PMID:24816275

VANLO - Interactive visual exploration of aligned biological networks

PubMed Central

Brasch, Steffen; Linsen, Lars; Fuellen, Georg

2009-01-01

Background Protein-protein interaction (PPI) is fundamental to many biological processes. In the course of evolution, biological networks such as protein-protein interaction networks have developed. Biological networks of different species can be aligned by finding instances (e.g. proteins) with the same common ancestor in the evolutionary process, so-called orthologs. For a better understanding of the evolution of biological networks, such aligned networks have to be explored. Visualization can play a key role in making the various relationships transparent. Results We present a novel visualization system for aligned biological networks in 3D space that naturally embeds existing 2D layouts. In addition to displaying the intra-network connectivities, we also provide insight into how the individual networks relate to each other by placing aligned entities on top of each other in separate layers. We optimize the layout of the entire alignment graph in a global fashion that takes into account inter- as well as intra-network relationships. The layout algorithm includes a step of merging aligned networks into one graph, laying out the graph with respect to application-specific requirements, splitting the merged graph again into individual networks, and displaying the network alignment in layers. In addition to representing the data in a static way, we also provide different interaction techniques to explore the data with respect to application-specific tasks. Conclusion Our system provides an intuitive global understanding of aligned PPI networks and it allows the investigation of key biological questions. We evaluate our system by applying it to real-world examples documenting how our system can be used to investigate the data with respect to these key questions. Our tool VANLO (Visualization of Aligned Networks with Layout Optimization) can be accessed at . PMID:19821976

Systemic Darwinism

PubMed Central

Winther, Rasmus Grønfeldt

2008-01-01

Darwin's 19th century evolutionary theory of descent with modification through natural selection opened up a multidimensional and integrative conceptual space for biology. We explore three dimensions of this space: explanatory pattern, levels of selection, and degree of difference among units of the same type. Each dimension is defined by a respective pair of poles: law and narrative explanation, organismic and hierarchical selection, and variational and essentialist thinking. As a consequence of conceptual debates in the 20th century biological sciences, the poles of each pair came to be seen as mutually exclusive opposites. A significant amount of 21st century research focuses on systems (e.g., genomic, cellular, organismic, and ecological/global). Systemic Darwinism is emerging in this context. It follows a “compositional paradigm” according to which complex systems and their hierarchical networks of parts are the focus of biological investigation. Through the investigation of systems, Systemic Darwinism promises to reintegrate each dimension of Darwin's original logical space. Moreover, this ideally and potentially unified theory of biological ontology coordinates and integrates a plurality of mathematical biological theories (e.g., self-organization/structure, cladistics/history, and evolutionary genetics/function). Integrative Systemic Darwinism requires communal articulation from a plurality of perspectives. Although it is more general than these, it draws on previous advances in Systems Theory, Systems Biology, and Hierarchy Theory. Systemic Darwinism would greatly further bioengineering research and would provide a significantly deeper and more critical understanding of biological reality. PMID:18697926

Systemic darwinism.

PubMed

Winther, Rasmus Grønfeldt

2008-08-19

Darwin's 19th century evolutionary theory of descent with modification through natural selection opened up a multidimensional and integrative conceptual space for biology. We explore three dimensions of this space: explanatory pattern, levels of selection, and degree of difference among units of the same type. Each dimension is defined by a respective pair of poles: law and narrative explanation, organismic and hierarchical selection, and variational and essentialist thinking. As a consequence of conceptual debates in the 20th century biological sciences, the poles of each pair came to be seen as mutually exclusive opposites. A significant amount of 21st century research focuses on systems (e.g., genomic, cellular, organismic, and ecological/global). Systemic Darwinism is emerging in this context. It follows a "compositional paradigm" according to which complex systems and their hierarchical networks of parts are the focus of biological investigation. Through the investigation of systems, Systemic Darwinism promises to reintegrate each dimension of Darwin's original logical space. Moreover, this ideally and potentially unified theory of biological ontology coordinates and integrates a plurality of mathematical biological theories (e.g., self-organization/structure, cladistics/history, and evolutionary genetics/function). Integrative Systemic Darwinism requires communal articulation from a plurality of perspectives. Although it is more general than these, it draws on previous advances in Systems Theory, Systems Biology, and Hierarchy Theory. Systemic Darwinism would greatly further bioengineering research and would provide a significantly deeper and more critical understanding of biological reality.

Preferential Edge Habitat Colonization by a Specialist Weevil, Rhinoncomimus latipes (Coleoptera: Curculionidae)

USDA-ARS?s Scientific Manuscript database

Understanding the behavioral basis of dispersal and colonization is critical in biological control systems, where success of a natural enemy depends in part on its ability to find and move to new host patches. We studied behavior of the specialist weevil Rhinoncomimus latipes Korotyaev, a biological...

Systems Biology Approaches for Host–Fungal Interactions: An Expanding Multi-Omics Frontier

PubMed Central

Culibrk, Luka; Croft, Carys A.

2016-01-01

Abstract Opportunistic fungal infections are an increasing threat for global health, and for immunocompromised patients in particular. These infections are characterized by interaction between fungal pathogen and host cells. The exact mechanisms and the attendant variability in host and fungal pathogen interaction remain to be fully elucidated. The field of systems biology aims to characterize a biological system, and utilize this knowledge to predict the system's response to stimuli such as fungal exposures. A multi-omics approach, for example, combining data from genomics, proteomics, metabolomics, would allow a more comprehensive and pan-optic “two systems” biology of both the host and the fungal pathogen. In this review and literature analysis, we present highly specialized and nascent methods for analysis of multiple -omes of biological systems, in addition to emerging single-molecule visualization techniques that may assist in determining biological relevance of multi-omics data. We provide an overview of computational methods for modeling of gene regulatory networks, including some that have been applied towards the study of an interacting host and pathogen. In sum, comprehensive characterizations of host–fungal pathogen systems are now possible, and utilization of these cutting-edge multi-omics strategies may yield advances in better understanding of both host biology and fungal pathogens at a systems scale. PMID:26885725

System Theory and Physiological Processes.

PubMed

Jones, R W

1963-05-03

Engineers and physiologists working together in experimental and theoretical studies predict that the application of system analysis to biological processes will increase understanding of these processes and broaden the base of system theory. Richard W. Jones, professor of electrical engineering at Northwestern University, Evanston, Illinois, and John S. Gray, professor of physiology at Northwestern's Medical School, discuss these developments. Their articles are adapted from addresses delivered in Chicago in November 1962 at the 15th Annual Conference on Engineering in Medicine and Biology.

Deriving principles of microbiology by multiscaling laws of molecular physics.

PubMed

Ortoleva, Peter; Adhangale, P; Cheluvaraja, S; Fontus, Max; Shreif, Zeina

2009-01-01

It has long been an objective of the physical sciences to derive principles of biology from the laws of physics. At the angstrom scale for processes evolving on timescales of 10(-14) s, many systems can be characterized in terms of atomic vibrations and collisions. In contrast, biological systems display dramatic transformations including self-assembly and reorganization from one cell phenotype to another as the microenvironment changes. We have developed a framework for understanding the emergence of living systems from the underlying atomic chaos.

At the Edge of Translation – Materials to Program Cells for Directed Differentiation

PubMed Central

Arany, Praveen R; Mooney, David J

2010-01-01

The rapid advancement in basic biology knowledge, especially in the stem cell field, has created new opportunities to develop biomaterials capable of orchestrating the behavior of transplanted and host cells. Based on our current understanding of cellular differentiation, a conceptual framework for the use of materials to program cells in situ is presented, namely a domino versus a switchboard model, to highlight the use of single versus multiple cues in a controlled manner to modulate biological processes. Further, specific design principles of material systems to present soluble and insoluble cues that are capable of recruiting, programming and deploying host cells for various applications are presented. The evolution of biomaterials from simple inert substances used to fill defects, to the recent development of sophisticated material systems capable of programming cells in situ is providing a platform to translate our understanding of basic biological mechanisms to clinical care. PMID:20860763

The Physics of Open Ended Evolution

NASA Astrophysics Data System (ADS)

Adams, Alyssa M.

What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed.

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

Managing biological networks by using text mining and computer-aided curation

NASA Astrophysics Data System (ADS)

Yu, Seok Jong; Cho, Yongseong; Lee, Min-Ho; Lim, Jongtae; Yoo, Jaesoo

2015-11-01

In order to understand a biological mechanism in a cell, a researcher should collect a huge number of protein interactions with experimental data from experiments and the literature. Text mining systems that extract biological interactions from papers have been used to construct biological networks for a few decades. Even though the text mining of literature is necessary to construct a biological network, few systems with a text mining tool are available for biologists who want to construct their own biological networks. We have developed a biological network construction system called BioKnowledge Viewer that can generate a biological interaction network by using a text mining tool and biological taggers. It also Boolean simulation software to provide a biological modeling system to simulate the model that is made with the text mining tool. A user can download PubMed articles and construct a biological network by using the Multi-level Knowledge Emergence Model (KMEM), MetaMap, and A Biomedical Named Entity Recognizer (ABNER) as a text mining tool. To evaluate the system, we constructed an aging-related biological network that consist 9,415 nodes (genes) by using manual curation. With network analysis, we found that several genes, including JNK, AP-1, and BCL-2, were highly related in aging biological network. We provide a semi-automatic curation environment so that users can obtain a graph database for managing text mining results that are generated in the server system and can navigate the network with BioKnowledge Viewer, which is freely available at http://bioknowledgeviewer.kisti.re.kr.

Understanding pictorial information in biology: students' cognitive activities and visual reading strategies

NASA Astrophysics Data System (ADS)

Brandstetter, Miriam; Sandmann, Angela; Florian, Christine

2017-06-01

In classroom, scientific contents are increasingly communicated through visual forms of representations. Students' learning outcomes rely on their ability to read and understand pictorial information. Understanding pictorial information in biology requires cognitive effort and can be challenging to students. Yet evidence-based knowledge about students' visual reading strategies during the process of understanding pictorial information is pending. Therefore, 42 students at the age of 14-15 were asked to think aloud while trying to understand visual representations of the blood circulatory system and the patellar reflex. A category system was developed differentiating 16 categories of cognitive activities. A Principal Component Analysis revealed two underlying patterns of activities that can be interpreted as visual reading strategies: 1. Inferences predominated by using a problem-solving schema; 2. Inferences predominated by recall of prior content knowledge. Each pattern consists of a specific set of cognitive activities that reflect selection, organisation and integration of pictorial information as well as different levels of expertise. The results give detailed insights into cognitive activities of students who were required to understand the pictorial information of complex organ systems. They provide an evidence-based foundation to derive instructional aids that can promote students pictorial-information-based learning on different levels of expertise.

Systems Biology, Systems Medicine, Systems Pharmacology: The What and The Why.

PubMed

Stéphanou, Angélique; Fanchon, Eric; Innominato, Pasquale F; Ballesta, Annabelle

2018-05-09

Systems biology is today such a widespread discipline that it becomes difficult to propose a clear definition of what it really is. For some, it remains restricted to the genomic field. For many, it designates the integrated approach or the corpus of computational methods employed to handle the vast amount of biological or medical data and investigate the complexity of the living. Although defining systems biology might be difficult, on the other hand its purpose is clear: systems biology, with its emerging subfields systems medicine and systems pharmacology, clearly aims at making sense of complex observations/experimental and clinical datasets to improve our understanding of diseases and their treatments without putting aside the context in which they appear and develop. In this short review, we aim to specifically focus on these new subfields with the new theoretical tools and approaches that were developed in the context of cancer. Systems pharmacology and medicine now give hope for major improvements in cancer therapy, making personalized medicine closer to reality. As we will see, the current challenge is to be able to improve the clinical practice according to the paradigm shift of systems sciences.

Single-molecule imaging in live bacteria cells.

PubMed

Ritchie, Ken; Lill, Yoriko; Sood, Chetan; Lee, Hochan; Zhang, Shunyuan

2013-02-05

Bacteria, such as Escherichia coli and Caulobacter crescentus, are the most studied and perhaps best-understood organisms in biology. The advances in understanding of living systems gained from these organisms are immense. Application of single-molecule techniques in bacteria have presented unique difficulties owing to their small size and highly curved form. The aim of this review is to show advances made in single-molecule imaging in bacteria over the past 10 years, and to look to the future where the combination of implementing such high-precision techniques in well-characterized and controllable model systems such as E. coli could lead to a greater understanding of fundamental biological questions inaccessible through classic ensemble methods.

Generalizing genetical genomics: getting added value from environmental perturbation.

PubMed

Li, Yang; Breitling, Rainer; Jansen, Ritsert C

2008-10-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across multiple environments. We propose a generalization of genetical genomics, which combines genetic and sensibly chosen environmental perturbations, to study the plasticity of molecular networks. This strategy forms a crucial step toward understanding why individuals respond differently to drugs, toxins, pathogens, nutrients and other environmental influences. Here we outline a strategy for selecting and allocating individuals to particular treatments, and we discuss the promises and pitfalls of the generalized genetical genomics approach.

Introductory Biology Students’ Use of Enhanced Answer Keys and Reflection Questions to Engage in Metacognition and Enhance Understanding

PubMed Central

Sabel, Jaime L.; Dauer, Joseph T.; Forbes, Cory T.

2017-01-01

Providing feedback to students as they learn to integrate individual concepts into complex systems is an important way to help them to develop robust understanding, but it is challenging in large, undergraduate classes for instructors to provide feedback that is frequent and directed enough to help individual students. Various scaffolds can be used to help students engage in self-regulated learning and generate internal feedback to improve their learning. This study examined the use of enhanced answer keys with added reflection questions and instruction as scaffolds for engaging undergraduate students in self-regulated learning within an introductory biology course. Study findings show that both the enhanced answer keys and reflection questions helped students to engage in metacognition and develop greater understanding of biological concepts. Further, students who received additional instruction on the use of the scaffolds changed how they used them and, by the end of the semester, were using the scaffolds in significantly different ways and showed significantly higher learning gains than students who did not receive the instruction. These findings provide evidence for the benefit of designing scaffolds within biology courses that will support students in engaging in metacognition and enhancing their understanding of biological concepts. PMID:28645893

Understanding water uptake in bioaerosols using laboratory measurements, field tests, and modeling

NASA Astrophysics Data System (ADS)

Chaudhry, Zahra; Ratnesar-Shumate, Shanna A.; Buckley, Thomas J.; Kalter, Jeffrey M.; Gilberry, Jerome U.; Eshbaugh, Jonathan P.; Corson, Elizabeth C.; Santarpia, Joshua L.; Carter, Christopher C.

2013-05-01

Uptake of water by biological aerosols can impact their physical and chemical characteristics. The water content in a bioaerosol can affect the backscatter cross-section as measured by LIDAR systems. Better understanding of the water content in controlled-release clouds of bioaerosols can aid in the development of improved standoff detection systems. This study includes three methods to improve understanding of how bioaerosols take up water. The laboratory method measures hygroscopic growth of biological material after it is aerosolized and dried. Hygroscopicity curves are created as the humidity is increased in small increments to observe the deliquescence point, then the humidity is decreased to observe the efflorescence point. The field component of the study measures particle size distributions of biological material disseminated into a large humidified chamber. Measurements are made with a Twin-Aerodynamic Particle Sizer (APS, TSI, Inc), -Relative Humidity apparatus where two APS units measure the same aerosol cloud side-by-side. The first operated under dry conditions by sampling downstream of desiccant dryers, the second operated under ambient conditions. Relative humidity was measured within the sampling systems to determine the difference in the aerosol water content between the two sampling trains. The water content of the bioaerosols was calculated from the twin APS units following Khlystov et al. 2005 [1]. Biological material is measured dried and wet and compared to laboratory curves of the same material. Lastly, theoretical curves are constructed from literature values for components of the bioaerosol material.

Native American Students' Understanding of Geologic Time Scale: 4th-8th Grade Ojibwe Students' Understanding of Earth's Geologic History

ERIC Educational Resources Information Center

Nam, Younkyeong; Karahan, Engin; Roehrig, Gillian

2016-01-01

Geologic time scale is a very important concept for understanding long-term earth system events such as climate change. This study examines forty-three 4th-8th grade Native American--particularly Ojibwe tribe--students' understanding of relative ordering and absolute time of Earth's significant geological and biological events. This study also…

Human development II: we need an integrated theory for matter, life and consciousness to understand life and healing.

PubMed

Ventegodt, Søren; Hermansen, Tyge Dahl; Nielsen, Maj Lyck; Clausen, Birgitte; Merrick, Joav

2006-07-06

For almost a decade, we have experimented with supporting the philosophical development of severely ill patients to induce recovery and spontaneous healing. Recently, we have observed a new pattern of extremely rapid, spontaneous healing that apparently can facilitate even the spontaneous remission of cancer and the spontaneous recovery of mental diseases like schizophrenia and borderline schizophrenia. Our working hypothesis is that the accelerated healing is a function of the patient's brain-mind and body-mind coming closer together due to the development of what we call "deep" cosmology. To understand and describe what happens at a biological level, we have suggested naming the process adult human metamorphosis, a possibility that is opened by the human genome showing full generic equipment for metamorphosis. To understand the mechanistic details in the complicated interaction between consciousness and biology, we need an adequate theory for biological information. In a series of papers, we propose what we call "holistic biology for holistic medicine". We suggest that a relatively simple model based on interacting wholenesses instead of isolated parts can shed a new light on a number of difficult issues that we need to explain and understand in biology and medicine in order to understand and use metamorphosis in the holistic medical clinic. We aim to give a holistic theoretical interpretation of biological phenomena at large, morphogenesis, evolution, immune system regulation (self-nonself discrimination), brain function, consciousness, and health in particular. We start at the most fundamental problem: what is biological information at the subcellular, cellular, and supracellular levels if we presume that it is the same phenomenon on all levels (using Occam's razor), and how can this be described scientifically? The problems we address are all connected to the information flow in the functioning, living organism: function of the brain and consciousness, the regulations of the immune system and cell growth, the dynamics of health and disease. We suggest that life utilizes an unseen fine structure of the physical energy of the universe at a subparticular or quantum level to give information-directed self-organization; we give a first sketch of a possible fractal structure of the energy able to both contain and communicate biological information and carry individual and collective consciousness. Finally, thorough our analysis, we put up a model for adult human metamorphosis.

Mammalian synthetic biology for studying the cell

PubMed Central

Mathur, Melina; Xiang, Joy S.

2017-01-01

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. PMID:27932576

Advancing "Bio" Sensor Integration with Ocean Observing Systems to Support Ecosystem Based Approaches

NASA Astrophysics Data System (ADS)

Moustahfid, H.; Michaels, W.

2016-02-01

The vision of the US Integrated Ocean Observing System (U.S. IOOS) is to provide information and services to the nation for enhancing our understanding of the ecosystem and climate; sustaining living marine resources; improving public health and safety; reducing impacts of natural hazards and environmental changes; and expanding support for marine commerce and transportation. In the last decade, U.S. IOOS has made considerable progress in advancing physical and chemical observing systems, while further efforts are needed to fully integrate biological observing systems into U.S. IOOS. Recent technological advances in miniature, low power "bio" sensors deployed from fixed and mobile autonomous platforms enable remote sensing of biological components ranging from plankton greater than 20 micrometer with electro-optical technology to meso-zooplankton and nekton with hydroacoustic technology. Satellite communication linked to sensing technologies provide near real-time information of the movement and behavior of the biological organisms including the large marine predators. This opens up remarkable opportunities for observing the biotic realm at critical spatio-temporal scales for understanding how environmental changes impact on the productivity and health of our oceans. Biosensor technology has matured to be operationally integrated into ocean observation systems to provide synoptic bio-physical monitoring information. The operational objectives should be clearly defined and implemented by biological and physical oceanographers to optimize the integration of biological observing into U.S IOOS which will strengthen the national observing capabilities in response to the increasing demand for ecosystem observations to support ecosystem-based approaches for the sustainability of living marine resources and healthy oceans.

Optimizing Introductory Physics for the Life Sciences: Placing Physics in Biological Context

NASA Astrophysics Data System (ADS)

Crouch, Catherine

2014-03-01

Physics is a critical foundation for today's life sciences and medicine. However, the physics content and ways of thinking identified by life scientists as most important for their fields are often not taught, or underemphasized, in traditional introductory physics courses. Furthermore, such courses rarely give students practice using physics to understand living systems in a substantial way. Consequently, students are unlikely to recognize the value of physics to their chosen fields, or to develop facility in applying physics to biological systems. At Swarthmore, as at several other institutions engaged in reforming this course, we have reorganized the introductory course for life science students around touchstone biological examples, in which fundamental physics contributes significantly to understanding biological phenomena or research techniques, in order to make explicit the value of physics to the life sciences. We have also focused on the physics topics and approaches most relevant to biology while seeking to develop rigorous qualitative reasoning and quantitative problem solving skills, using established pedagogical best practices. Each unit is motivated by and culminates with students analyzing one or more touchstone examples. For example, in the second semester we emphasize electric potential and potential difference more than electric field, and start from students' typically superficial understanding of the cell membrane potential and of electrical interactions in biochemistry to help them develop a more sophisticated understanding of electric forces, field, and potential, including in the salt water environment of life. Other second semester touchstones include optics of vision and microscopes, circuit models for neural signaling, and magnetotactic bacteria. When possible, we have adapted existing research-based curricular materials to support these examples. This talk will describe the design and development process for this course, give examples of materials, and present initial assessment data evaluating both content learning and student attitudes.

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns

PubMed Central

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning. PMID:29209191

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

PubMed

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

Biomedical implications of information processing in chemical systems: non-classical approach to photochemistry of coordination compounds.

PubMed

Szaciłowski, Konrad

2007-01-01

Analogies between photoactive nitric oxide generators and various electronic devices: logic gates and operational amplifiers are presented. These analogies have important biological consequences: application of control parameters allows for better targeting and control of nitric oxide drugs. The same methodology may be applied in the future for other therapeutic strategies and at the same time helps to understand natural regulatory and signaling processes in biological systems.

An outlook review: mechanochromic materials and their potential for biological and healthcare applications.

PubMed

Jiang, Ying

2014-12-01

Macroscopic mechanical perturbations have been observed to result in optical changes for certain compounds and composite materials. This phenomenon could originate from chemical and physical changes across various length scales, from the rearrangement of chemical bonds to alteration of molecular domains on the order of several hundred nanometers. This review classifies the mechanisms and surveys of how each class of mechanochromic materials has been, and can potentially be applied in biological and healthcare innovations. The study of cellular and molecular responses to mechanical forces in biological systems is an emerging field; there is potential in applying mechanochromic principles and material systems for probing biological systems. On the other hand, application of mechanochromic materials for medical and healthcare consumer products has been described in a wide variety of concepts and inventions. It is hopeful that further understanding of mechanochromism and material innovations would initiate concrete, impactful studies in biological systems soon. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

Predictive ecology: systems approaches

PubMed Central

Evans, Matthew R.; Norris, Ken J.; Benton, Tim G.

2012-01-01

The world is experiencing significant, largely anthropogenically induced, environmental change. This will impact on the biological world and we need to be able to forecast its effects. In order to produce such forecasts, ecology needs to become more predictive—to develop the ability to understand how ecological systems will behave in future, changed, conditions. Further development of process-based models is required to allow such predictions to be made. Critical to the development of such models will be achieving a balance between the brute-force approach that naively attempts to include everything, and over simplification that throws out important heterogeneities at various levels. Central to this will be the recognition that individuals are the elementary particles of all ecological systems. As such it will be necessary to understand the effect of evolution on ecological systems, particularly when exposed to environmental change. However, insights from evolutionary biology will help the development of models even when data may be sparse. Process-based models are more common, and are used for forecasting, in other disciplines, e.g. climatology and molecular systems biology. Tools and techniques developed in these endeavours can be appropriated into ecological modelling, but it will also be necessary to develop the science of ecoinformatics along with approaches specific to ecological problems. The impetus for this effort should come from the demand coming from society to understand the effects of environmental change on the world and what might be performed to mitigate or adapt to them. PMID:22144379

Systems biology: A tool for charting the antiviral landscape.

PubMed

Bowen, James R; Ferris, Martin T; Suthar, Mehul S

2016-06-15

The host antiviral programs that are initiated following viral infection form a dynamic and complex web of responses that we have collectively termed as "the antiviral landscape". Conventional approaches to studying antiviral responses have primarily used reductionist systems to assess the function of a single or a limited subset of molecules. Systems biology is a holistic approach that considers the entire system as a whole, rather than individual components or molecules. Systems biology based approaches facilitate an unbiased and comprehensive analysis of the antiviral landscape, while allowing for the discovery of emergent properties that are missed by conventional approaches. The antiviral landscape can be viewed as a hierarchy of complexity, beginning at the whole organism level and progressing downward to isolated tissues, populations of cells, and single cells. In this review, we will discuss how systems biology has been applied to better understand the antiviral landscape at each of these layers. At the organismal level, the Collaborative Cross is an invaluable genetic resource for assessing how genetic diversity influences the antiviral response. Whole tissue and isolated bulk cell transcriptomics serves as a critical tool for the comprehensive analysis of antiviral responses at both the tissue and cellular levels of complexity. Finally, new techniques in single cell analysis are emerging tools that will revolutionize our understanding of how individual cells within a bulk infected cell population contribute to the overall antiviral landscape. Copyright © 2016 Elsevier B.V. All rights reserved.

Discovering the intelligence in molecular biology.

PubMed

Uberbacher, E

1995-12-01

The Third International Conference on Intelligent Systems in Molecular Biology was truly an outstanding event. Computational methods in molecular biology have reached a new level of maturity and utility, resulting in many high-impact applications. The success of this meeting bodes well for the rapid and continuing development of computational methods, intelligent systems and information-based approaches for the biosciences. The basic technology, originally most often applied to 'feasibility' problems, is now dealing effectively with the most difficult real-world problems. Significant progress has been made in understanding protein-structure information, structural classification, and how functional information and the relevant features of active-site geometry can be gleaned from structures by automated computational approaches. The value and limits of homology-based methods, and the ability to classify proteins by structure in the absence of homology, have reached a new level of sophistication. New methods for covariation analysis in the folding of large structures such as RNAs have shown remarkably good results, indicating the long-term potential to understand very complicated molecules and multimolecular complexes using computational means. Novel methods, such as HMMs, context-free grammars and the uses of mutual information theory, have taken center stage as highly valuable tools in our quest to represent and characterize biological information. A focus on creative uses of intelligent systems technologies and the trend toward biological application will undoubtedly continue and grow at the 1996 ISMB meeting in St Louis.

Systems biology of meridians, acupoints, and chinese herbs in disease.

PubMed

Lin, Li-Ling; Wang, Ya-Hui; Lai, Chi-Yu; Chau, Chan-Lao; Su, Guan-Chin; Yang, Chun-Yi; Lou, Shu-Ying; Chen, Szu-Kai; Hsu, Kuan-Hao; Lai, Yen-Ling; Wu, Wei-Ming; Huang, Jian-Long; Liao, Chih-Hsin; Juan, Hsueh-Fen

2012-01-01

Meridians, acupoints, and Chinese herbs are important components of traditional Chinese medicine (TCM). They have been used for disease treatment and prevention and as alternative and complementary therapies. Systems biology integrates omics data, such as transcriptional, proteomic, and metabolomics data, in order to obtain a more global and complete picture of biological activity. To further understand the existence and functions of the three components above, we reviewed relevant research in the systems biology literature and found many recent studies that indicate the value of acupuncture and Chinese herbs. Acupuncture is useful in pain moderation and relieves various symptoms arising from acute spinal cord injury and acute ischemic stroke. Moreover, Chinese herbal extracts have been linked to wound repair, the alleviation of postmenopausal osteoporosis severity, and anti-tumor effects, among others. Different acupoints, variations in treatment duration, and herbal extracts can be used to alleviate various symptoms and conditions and to regulate biological pathways by altering gene and protein expression. Our paper demonstrates how systems biology has helped to establish a platform for investigating the efficacy of TCM in treating different diseases and improving treatment strategies.

Electronic health records (EHRs): supporting ASCO's vision of cancer care.

PubMed

Yu, Peter; Artz, David; Warner, Jeremy

2014-01-01

ASCO's vision for cancer care in 2030 is built on the expanding importance of panomics and big data, and envisions enabling better health for patients with cancer by the rapid transformation of systems biology knowledge into cancer care advances. This vision will be heavily dependent on the use of health information technology for computational biology and clinical decision support systems (CDSS). Computational biology will allow us to construct models of cancer biology that encompass the complexity of cancer panomics data and provide us with better understanding of the mechanisms governing cancer behavior. The Agency for Healthcare Research and Quality promotes CDSS based on clinical practice guidelines, which are knowledge bases that grow too slowly to match the rate of panomic-derived knowledge. CDSS that are based on systems biology models will be more easily adaptable to rapid advancements and translational medicine. We describe the characteristics of health data representation, a model for representing molecular data that supports data extraction and use for panomic-based clinical research, and argue for CDSS that are based on systems biology and are algorithm-based.

The edges of understanding.

PubMed

Lander, Arthur D

2010-04-12

A culture's icons are a window onto its soul. Few would disagree that, in the culture of molecular biology that dominated much of the life sciences for the last third of the 20th century, the dominant icon was the double helix. In the present, post-modern, 'systems biology' era, however, it is, arguably, the hairball.

Global Change: A Biogeochemical Perspective

NASA Technical Reports Server (NTRS)

Mcelroy, M.

1983-01-01

A research program that is designed to enhance our understanding of the Earth as the support system for life is described. The program change, both natural and anthropogenic, that might affect the habitability of the planet on a time scale roughly equal to that of a human life is studied. On this time scale the atmosphere, biosphere, and upper ocean are treated as a single coupled system. The need for understanding the processes affecting the distribution of essential nutrients--carbon, nitrogen, phosphorous, sulfur, and water--within this coupled system is examined. The importance of subtle interactions among chemical, biological, and physical effects is emphasized. The specific objectives are to define the present state of the planetary life-support system; to ellucidate the underlying physical, chemical, and biological controls; and to provide the body of knowledge required to assess changes that might impact the future habitability of the Earth.

Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is.

PubMed

Benson, Neil

2015-08-01

Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pacific Northwest Laboratory annual report for 1993 to the DOE Office of Energy Research. Part 1: Biomedical Sciences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lumetta, C.C.; Park, J.F.

1994-03-01

This report summarizes FY 1993 progress in biological and general life sciences research programs conducted for the Department of Energy`s Office of Health and Environmental REsearch (OHER) at Pacific Northwest Laboratory (PNL). This research provides knowledge of fundamental principles necessary to identify, understand, and anticipate the long-term health consequences of exposure to energy-related radiation and chemicals. The Biological Research section contains reports of studies using laboratory animals, in vitro cell systems, and molecular biological systems. This research includes studies of the impact of radiation, radionuclides, and chemicals on biological responses at all levels of biological organization. The General Life Sciencesmore » Research section reports research conducted for the OHER human genome program.« less

Molecular Force Spectroscopy on Cells

NASA Astrophysics Data System (ADS)

Liu, Baoyu; Chen, Wei; Zhu, Cheng

2015-04-01

Molecular force spectroscopy has become a powerful tool to study how mechanics regulates biology, especially the mechanical regulation of molecular interactions and its impact on cellular functions. This force-driven methodology has uncovered a wealth of new information of the physical chemistry of molecular bonds for various biological systems. The new concepts, qualitative and quantitative measures describing bond behavior under force, and structural bases underlying these phenomena have substantially advanced our fundamental understanding of the inner workings of biological systems from the nanoscale (molecule) to the microscale (cell), elucidated basic molecular mechanisms of a wide range of important biological processes, and provided opportunities for engineering applications. Here, we review major force spectroscopic assays, conceptual developments of mechanically regulated kinetics of molecular interactions, and their biological relevance. We also present current challenges and highlight future directions.

The relativity of biological function.

PubMed

Laubichler, Manfred D; Stadler, Peter F; Prohaska, Sonja J; Nowick, Katja

2015-12-01

Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

Understanding Biological Rates and their Temperature Dependence, from Enzymes to Ecosystems

NASA Astrophysics Data System (ADS)

Prentice, E.; Arcus, V. L.

2017-12-01

Temperature responses over various scales in biological systems follow a similar pattern; negative curvature results in an optimum temperature (Topt) for activity/growth/turnover, with decreases in rates on either side of Topt. Previously this downturn in rates at high temperatures has been attributed to enzyme denaturation, where a failing of the basic driving units of metabolism was used to describe curvature at the enzyme and organism level. However, recent developments in our understanding of the factors governing enzyme rates at different temperatures have guided a new understanding of the responses of biological systems. Enzymes catalyse reactions by driving the substrate through a high energy species, which is tightly bound to the enzyme. Macromolecular rate theory (MMRT) has recently been developed to account for the changes in the system brought about by this tight binding, specifically the change in the physical parameter heat capacity (ΔCǂp), and the effect this has on the temperature dependence of enzyme reactions. A negative ΔCǂp imparts the signature negative curvature to rates in the absence of denaturation, and finds that Topt, ΔCǂp and curvature are all correlated, placing constraints on biological systems. The simplest of cells comprise thousands of enzymatically catalysed reactions, functioning in series and in parallel in metabolic pathways to determine the overall growth rate of an organism. Intuitively, the temperature effects of enzymes play a role in determining the overall temperature dependence of an organism, in tandem with cellular level regulatory responses. However, the effect of individual Topt values and curvature on overall pathway behaviour is less apparent. Here, this is investigated in the context of MMRT through the in vitro characterisation of a six-step metabolic pathway to understand the steps in isolation and functioning in series. Pathway behaviour is found to be approximately an average of the properties of the individual steps, indicating all enzymes have an influence on organism temperature dependence. This has implications for our understanding of how organisms respond to fluctuations in environmental temperature.

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

[Chronobiology of immune system].

PubMed

Trufakin, V A; Shurlygina, A V; Dergacheva, T I; Litvinenko, G I; Verbitskaia, L V

1999-01-01

The biological rhythmological programme of the immune system is a constituent of the body's common biological rhythmological programme. Its pattern seems to be genetically determined and reflects the functional status of the system. The chronobiological mechanisms responsible for the regulation of immune functions lie in the presence of certain phasic interrelations between the biological rhythms of the synthesis and production of regulatory agents on the one hand, and those of the receptor system and metabolic potential of immunocompetent cells on the other. The facts given in the paper may be a basis for a chronobiological approach to better understanding the mechanisms of the physiology and pathology of the immune system. The medical significance of study of the structural and temporal pattern of the immune system consists in the development of new techniques for diagnosis, prognosis, therapy, and assessment of risk factors in immunopathological conditions.

Connections Matter: Social Networks and Lifespan Health in Primate Translational Models

PubMed Central

McCowan, Brenda; Beisner, Brianne; Bliss-Moreau, Eliza; Vandeleest, Jessica; Jin, Jian; Hannibal, Darcy; Hsieh, Fushing

2016-01-01

Humans live in societies full of rich and complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems that contribute to disease processes, including the mechanisms underlying the influence of social contexts on these biological systems. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health. PMID:27148103

Understanding the biological underpinnings of ecohydrological processes

NASA Astrophysics Data System (ADS)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation has precluded determination of sufficient theoretical development. Understanding the land-surface response and feedback to climate change requires a mechanistic understanding of the coupling of ecological and hydrological processes and an expansion of theory from the life sciences to appropriately contribute to the broader Earth system science goal.

Bird-nest puzzle: can the study of unisexual flowers such as cucumber solve the problem of plant sex determination?

PubMed

Bai, Shu-Nong; Xu, Zhi-Hong

2012-06-01

Unisexual flower development has long been used as a model system to understand the mechanism of plant sex determination. However, based on our investigation of the mechanisms regulating the development of unisexual cucumber flowers, we have realized that understanding how organ development is inhibited may not necessarily reveal how an organ is formed. We refer to this problem as a "bird-nest puzzle," meaning one cannot understand how a bird lays and hatches its eggs by understanding how its nest is ruined. To understand the biological significance of unisexual flowers, we reexamine the original meaning of sex and its application in plants. Additionally, we propose that the fundamental biological advantage for the selection and maintenance of unisexual flowers during evolution is to promote cross pollination.

Diversified Control Paths: A Significant Way Disease Genes Perturb the Human Regulatory Network

PubMed Central

Wang, Bingbo; Gao, Lin; Zhang, Qingfang; Li, Aimin; Deng, Yue; Guo, Xingli

2015-01-01

Background The complexity of biological systems motivates us to use the underlying networks to provide deep understanding of disease etiology and the human diseases are viewed as perturbations of dynamic properties of networks. Control theory that deals with dynamic systems has been successfully used to capture systems-level knowledge in large amount of quantitative biological interactions. But from the perspective of system control, the ways by which multiple genetic factors jointly perturb a disease phenotype still remain. Results In this work, we combine tools from control theory and network science to address the diversified control paths in complex networks. Then the ways by which the disease genes perturb biological systems are identified and quantified by the control paths in a human regulatory network. Furthermore, as an application, prioritization of candidate genes is presented by use of control path analysis and gene ontology annotation for definition of similarities. We use leave-one-out cross-validation to evaluate the ability of finding the gene-disease relationship. Results have shown compatible performance with previous sophisticated works, especially in directed systems. Conclusions Our results inspire a deeper understanding of molecular mechanisms that drive pathological processes. Diversified control paths offer a basis for integrated intervention techniques which will ultimately lead to the development of novel therapeutic strategies. PMID:26284649

Genes of innate immunity and the biological response to inhaled ozone

PubMed Central

Li, Zhuowei; Tighe, Robert M.; Feng, Feifei; Ledford, Julie G.; Hollingsworth, John W.

2013-01-01

Ambient ozone has a significant impact on human health. We have made considerable progress in understanding the fundamental mechanisms that regulate the biological response to ozone. It is increasingly clear that genes of innate immunity play a central role in both infectious and non-infectious lung disease. The biological response to ambient ozone provides a clinically relevant environmental exposure that allows us to better understand the role of innate immunity in non-infectious airways disease. In this brief review, we focus on: (1) specific cell types in the lung modified by ozone; (2) ozone and oxidative stress; (3) the relationship between genes of innate immunity and ozone; (4) the role of extracellular matrix in reactive airways disease; and (5) the effect of ozone on the adaptive immune system. We summarize recent advances in understanding the mechanisms that ozone contributes to environmental airways disease. PMID:23169704

Metabolomics: the apogee of the omic triology

PubMed Central

Patti, Gary J; Yanes, Oscar; Siuzdak, Gary

2013-01-01

Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and shaping our understanding of cell biology, physiology, and medicine. PMID:22436749

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Systems biology: An emerging strategy for discovering novel pathogenetic mechanisms that promote cardiovascular disease.

PubMed

Maron, Bradley A; Leopold, Jane A

2016-09-30

Reductionist theory proposes that analyzing complex systems according to their most fundamental components is required for problem resolution, and has served as the cornerstone of scientific methodology for more than four centuries. However, technological gains in the current scientific era now allow for the generation of large datasets that profile the proteomic, genomic, and metabolomic signatures of biological systems across a range of conditions. The accessibility of data on such a vast scale has, in turn, highlighted the limitations of reductionism, which is not conducive to analyses that consider multiple and contemporaneous interactions between intermediates within a pathway or across constructs. Systems biology has emerged as an alternative approach to analyze complex biological systems. This methodology is based on the generation of scale-free networks and, thus, provides a quantitative assessment of relationships between multiple intermediates, such as protein-protein interactions, within and between pathways of interest. In this way, systems biology is well positioned to identify novel targets implicated in the pathogenesis or treatment of diseases. In this review, the historical root and fundamental basis of systems biology, as well as the potential applications of this methodology are discussed with particular emphasis on integration of these concepts to further understanding of cardiovascular disorders such as coronary artery disease and pulmonary hypertension.

Circadian systems biology in Metazoa.

PubMed

Lin, Li-Ling; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2015-11-01

Systems biology, which can be defined as integrative biology, comprises multistage processes that can be used to understand components of complex biological systems of living organisms and provides hierarchical information to decoding life. Using systems biology approaches such as genomics, transcriptomics and proteomics, it is now possible to delineate more complicated interactions between circadian control systems and diseases. The circadian rhythm is a multiscale phenomenon existing within the body that influences numerous physiological activities such as changes in gene expression, protein turnover, metabolism and human behavior. In this review, we describe the relationships between the circadian control system and its related genes or proteins, and circadian rhythm disorders in systems biology studies. To maintain and modulate circadian oscillation, cells possess elaborative feedback loops composed of circadian core proteins that regulate the expression of other genes through their transcriptional activities. The disruption of these rhythms has been reported to be associated with diseases such as arrhythmia, obesity, insulin resistance, carcinogenesis and disruptions in natural oscillations in the control of cell growth. This review demonstrates that lifestyle is considered as a fundamental factor that modifies circadian rhythm, and the development of dysfunctions and diseases could be regulated by an underlying expression network with multiple circadian-associated signals. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Introductory Biology Students' Use of Enhanced Answer Keys and Reflection Questions to Engage in Metacognition and Enhance Understanding.

PubMed

Sabel, Jaime L; Dauer, Joseph T; Forbes, Cory T

2017-01-01

Providing feedback to students as they learn to integrate individual concepts into complex systems is an important way to help them to develop robust understanding, but it is challenging in large, undergraduate classes for instructors to provide feedback that is frequent and directed enough to help individual students. Various scaffolds can be used to help students engage in self-regulated learning and generate internal feedback to improve their learning. This study examined the use of enhanced answer keys with added reflection questions and instruction as scaffolds for engaging undergraduate students in self-regulated learning within an introductory biology course. Study findings show that both the enhanced answer keys and reflection questions helped students to engage in metacognition and develop greater understanding of biological concepts. Further, students who received additional instruction on the use of the scaffolds changed how they used them and, by the end of the semester, were using the scaffolds in significantly different ways and showed significantly higher learning gains than students who did not receive the instruction. These findings provide evidence for the benefit of designing scaffolds within biology courses that will support students in engaging in metacognition and enhancing their understanding of biological concepts. © 2017 J. L. Sabel et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

How sulphate-reducing microorganisms cope with stress: Lessons from systems biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, J.; He, Q.; Hemme, C.L.

2011-04-01

Sulphate-reducing microorganisms (SRMs) are a phylogenetically diverse group of anaerobes encompassing distinct physiologies with a broad ecological distribution. As SRMs have important roles in the biogeochemical cycling of carbon, nitrogen, sulphur and various metals, an understanding of how these organisms respond to environmental stresses is of fundamental and practical importance. In this Review, we highlight recent applications of systems biology tools in studying the stress responses of SRMs, particularly Desulfovibrio spp., at the cell, population, community and ecosystem levels. The syntrophic lifestyle of SRMs is also discussed, with a focus on system-level analyses of adaptive mechanisms. Such information is importantmore » for understanding the microbiology of the global sulphur cycle and for developing biotechnological applications of SRMs for environmental remediation, energy production, biocorrosion control, wastewater treatment and mineral recovery.« less

Taking Systems Medicine to Heart.

PubMed

Trachana, Kalliopi; Bargaje, Rhishikesh; Glusman, Gustavo; Price, Nathan D; Huang, Sui; Hood, Leroy E

2018-04-27

Systems medicine is a holistic approach to deciphering the complexity of human physiology in health and disease. In essence, a living body is constituted of networks of dynamically interacting units (molecules, cells, organs, etc) that underlie its collective functions. Declining resilience because of aging and other chronic environmental exposures drives the system to transition from a health state to a disease state; these transitions, triggered by acute perturbations or chronic disturbance, manifest as qualitative shifts in the interactions and dynamics of the disease-perturbed networks. Understanding health-to-disease transitions poses a high-dimensional nonlinear reconstruction problem that requires deep understanding of biology and innovation in study design, technology, and data analysis. With a focus on the principles of systems medicine, this Review discusses approaches for deciphering this biological complexity from a novel perspective, namely, understanding how disease-perturbed networks function; their study provides insights into fundamental disease mechanisms. The immediate goals for systems medicine are to identify early transitions to cardiovascular (and other chronic) diseases and to accelerate the translation of new preventive, diagnostic, or therapeutic targets into clinical practice, a critical step in the development of personalized, predictive, preventive, and participatory (P4) medicine. © 2018 American Heart Association, Inc.

Defence mechanisms: the role of physiology in current and future environmental protection paradigms

PubMed Central

Glover, Chris N

2018-01-01

Abstract Ecological risk assessments principally rely on simplified metrics of organismal sensitivity that do not consider mechanism or biological traits. As such, they are unable to adequately extrapolate from standard laboratory tests to real-world settings, and largely fail to account for the diversity of organisms and environmental variables that occur in natural environments. However, an understanding of how stressors influence organism health can compensate for these limitations. Mechanistic knowledge can be used to account for species differences in basal biological function and variability in environmental factors, including spatial and temporal changes in the chemical, physical and biological milieu. Consequently, physiological understanding of biological function, and how this is altered by stressor exposure, can facilitate proactive, predictive risk assessment. In this perspective article, existing frameworks that utilize physiological knowledge (e.g. biotic ligand models, adverse outcomes pathways and mechanistic effect models), are outlined, and specific examples of how mechanistic understanding has been used to predict risk are highlighted. Future research approaches and data needs for extending the incorporation of physiological information into ecological risk assessments are discussed. Although the review focuses on chemical toxicants in aquatic systems, physical and biological stressors and terrestrial environments are also briefly considered. PMID:29564135

Systems biology of cancer biomarker detection.

PubMed

Mitra, Sanga; Das, Smarajit; Chakrabarti, Jayprokas

2013-01-01

Cancer systems-biology is an ever-growing area of research due to explosion of data; how to mine these data and extract useful information is the problem. To have an insight on carcinogenesis one need to systematically mine several resources, such as databases, microarray and next-generation sequences. This review encompasses management and analysis of cancer data, databases construction and data deposition, whole transcriptome and genome comparison, analysing results from high throughput experiments to uncover cellular pathways and molecular interactions, and the design of effective algorithms to identify potential biomarkers. Recent technical advances such as ChIP-on-chip, ChIP-seq and RNA-seq can be applied to get epigenetic information transformed into a high-throughput endeavour to which systems biology and bioinformatics are making significant inroads. The data from ENCODE and GENCODE projects available through UCSC genome browser can be considered as benchmark for comparison and meta-analysis. A pipeline for integrating next generation sequencing data, microarray data, and putting them together with the existing database is discussed. The understanding of cancer genomics is changing the way we approach cancer diagnosis and treatment. To give a better understanding of utilizing available resources' we have chosen oral cancer to show how and what kind of analysis can be done. This review is a computational genomic primer that provides a bird's eye view of computational and bioinformatics' tools currently available to perform integrated genomic and system biology analyses of several carcinoma.

New and improved proteomics technologies for understanding complex biological systems: Addressing a grand challenge in the life sciences

PubMed Central

Hood, Leroy E.; Omenn, Gilbert S.; Moritz, Robert L.; Aebersold, Ruedi; Yamamoto, Keith R.; Amos, Michael; Hunter-Cevera, Jennie; Locascio, Laurie

2014-01-01

This White Paper sets out a Life Sciences Grand Challenge for Proteomics Technologies to enhance our understanding of complex biological systems, link genomes with phenotypes, and bring broad benefits to the biosciences and the US economy. The paper is based on a workshop hosted by the National Institute of Standards and Technology (NIST) in Gaithersburg, MD, 14–15 February 2011, with participants from many federal R&D agencies and research communities, under the aegis of the US National Science and Technology Council (NSTC). Opportunities are identified for a coordinated R&D effort to achieve major technology-based goals and address societal challenges in health, agriculture, nutrition, energy, environment, national security, and economic development. PMID:22807061

Comprehensive Evaluation of Biological Growth Control by Chlorine-Based Biocides in Power Plant Cooling Systems Using Tertiary Effluent

PubMed Central

Chien, Shih-Hsiang; Dzombak, David A.; Vidic, Radisav D.

2013-01-01

Abstract Recent studies have shown that treated municipal wastewater can be a reliable cooling water alternative to fresh water. However, elevated nutrient concentration and microbial population in wastewater lead to aggressive biological proliferation in the cooling system. Three chlorine-based biocides were evaluated for the control of biological growth in cooling systems using tertiary treated wastewater as makeup, based on their biocidal efficiency and cost-effectiveness. Optimal chemical regimens for achieving successful biological growth control were elucidated based on batch-, bench-, and pilot-scale experiments. Biocide usage and biological activity in planktonic and sessile phases were carefully monitored to understand biological growth potential and biocidal efficiency of the three disinfectants in this particular environment. Water parameters, such as temperature, cycles of concentration, and ammonia concentration in recirculating water, critically affected the biocide performance in recirculating cooling systems. Bench-scale recirculating tests were shown to adequately predict the biocide residual required for a pilot-scale cooling system. Optimal residuals needed for proper biological growth control were 1, 2–3, and 0.5–1 mg/L as Cl2 for NaOCl, preformed NH2Cl, and ClO2, respectively. Pilot-scale tests also revealed that Legionella pneumophila was absent from these cooling systems when using the disinfectants evaluated in this study. Cost analysis showed that NaOCl is the most cost-effective for controlling biological growth in power plant recirculating cooling systems using tertiary-treated wastewater as makeup. PMID:23781129

Comprehensive Evaluation of Biological Growth Control by Chlorine-Based Biocides in Power Plant Cooling Systems Using Tertiary Effluent.

PubMed

Chien, Shih-Hsiang; Dzombak, David A; Vidic, Radisav D

2013-06-01

Recent studies have shown that treated municipal wastewater can be a reliable cooling water alternative to fresh water. However, elevated nutrient concentration and microbial population in wastewater lead to aggressive biological proliferation in the cooling system. Three chlorine-based biocides were evaluated for the control of biological growth in cooling systems using tertiary treated wastewater as makeup, based on their biocidal efficiency and cost-effectiveness. Optimal chemical regimens for achieving successful biological growth control were elucidated based on batch-, bench-, and pilot-scale experiments. Biocide usage and biological activity in planktonic and sessile phases were carefully monitored to understand biological growth potential and biocidal efficiency of the three disinfectants in this particular environment. Water parameters, such as temperature, cycles of concentration, and ammonia concentration in recirculating water, critically affected the biocide performance in recirculating cooling systems. Bench-scale recirculating tests were shown to adequately predict the biocide residual required for a pilot-scale cooling system. Optimal residuals needed for proper biological growth control were 1, 2-3, and 0.5-1 mg/L as Cl 2 for NaOCl, preformed NH 2 Cl, and ClO 2 , respectively. Pilot-scale tests also revealed that Legionella pneumophila was absent from these cooling systems when using the disinfectants evaluated in this study. Cost analysis showed that NaOCl is the most cost-effective for controlling biological growth in power plant recirculating cooling systems using tertiary-treated wastewater as makeup.

Hemojuvelin-hepcidin axis modeled and analyzed using Petri nets.

PubMed

Formanowicz, Dorota; Kozak, Adam; Głowacki, Tomasz; Radom, Marcin; Formanowicz, Piotr

2013-12-01

Systems biology approach to investigate biological phenomena seems to be very promising because it is capable to capture one of the fundamental properties of living organisms, i.e. their inherent complexity. It allows for analysis biological entities as complex systems of interacting objects. The first and necessary step of such an analysis is building a precise model of the studied biological system. This model is expressed in the language of some branch of mathematics, as for example, differential equations. During the last two decades the theory of Petri nets has appeared to be very well suited for building models of biological systems. The structure of these nets reflects the structure of interacting biological molecules and processes. Moreover, on one hand, Petri nets have intuitive graphical representation being very helpful in understanding the structure of the system and on the other hand, there is a lot of mathematical methods and software tools supporting an analysis of the properties of the nets. In this paper a Petri net based model of the hemojuvelin-hepcidin axis involved in the maintenance of the human body iron homeostasis is presented. The analysis based mainly on T-invariants of the model properties has been made and some biological conclusions have been drawn. Copyright © 2013 Elsevier Inc. All rights reserved.

Understanding genetic variation - the value of systems biology.

PubMed

Hütt, Marc-Thorsten

2014-04-01

Pharmacology is currently transformed by the vast amounts of genome-associated information available for system-level interpretation. Here I review the potential of systems biology to facilitate this interpretation, thus paving the way for the emerging field of systems pharmacology. In particular, I will show how gene regulatory and metabolic networks can serve as a framework for interpreting high throughput data and as an interface to detailed dynamical models. In addition to the established connectivity analyses of effective networks, I suggest here to also analyze higher order architectural properties of effective networks. © 2013 The British Pharmacological Society.

A systems biology approach to invasive behavior: comparing cancer metastasis and suburban sprawl development

PubMed Central

2010-01-01

Background Despite constant progress, cancer remains the second leading cause of death in the United States. The ability of tumors to metastasize is central to this dilemma, as many studies demonstrate successful treatment correlating to diagnosis prior to cancer spread. Hence a better understanding of cancer invasiveness and metastasis could provide critical insight. Presentation of the hypothesis We hypothesize that a systems biology-based comparison of cancer invasiveness and suburban sprawl will reveal similarities that are instructive. Testing the hypothesis We compare the structure and behavior of invasive cancer to suburban sprawl development. While these two systems differ vastly in dimension, they appear to adhere to scale-invariant laws consistent with invasive behavior in general. We demonstrate that cancer and sprawl have striking similarities in their natural history, initiating factors, patterns of invasion, vessel distribution and even methods of causing death. Implications of the hypothesis We propose that metastatic cancer and suburban sprawl provide striking analogs in invasive behavior, to the extent that conclusions from one system could be predictive of behavior in the other. We suggest ways in which this model could be used to advance our understanding of cancer biology and treatment. PMID:20181145

Non-equilibrium assembly of microtubules: from molecules to autonomous chemical robots.

PubMed

Hess, H; Ross, Jennifer L

2017-09-18

Biological systems have evolved to harness non-equilibrium processes from the molecular to the macro scale. It is currently a grand challenge of chemistry, materials science, and engineering to understand and mimic biological systems that have the ability to autonomously sense stimuli, process these inputs, and respond by performing mechanical work. New chemical systems are responding to the challenge and form the basis for future responsive, adaptive, and active materials. In this article, we describe a particular biochemical-biomechanical network based on the microtubule cytoskeletal filament - itself a non-equilibrium chemical system. We trace the non-equilibrium aspects of the system from molecules to networks and describe how the cell uses this system to perform active work in essential processes. Finally, we discuss how microtubule-based engineered systems can serve as testbeds for autonomous chemical robots composed of biological and synthetic components.

Mammalian synthetic biology for studying the cell.

PubMed

Mathur, Melina; Xiang, Joy S; Smolke, Christina D

2017-01-02

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

Dynamical systems in economics

NASA Astrophysics Data System (ADS)

Stanojević, Jelena; Kukić, Katarina

2018-01-01

In last few decades much attention is given to explain complex behaviour of very large systems, such as weather, economy, biology and demography. In this paper we give short overview of basic notions in the field of dynamical systems which are relevant for understanding complex nature of some economic models.

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Biological neural networks as model systems for designing future parallel processing computers

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

One of the more interesting debates of the present day centers on whether human intelligence can be simulated by computer. The author works under the premise that neurons individually are not smart at all. Rather, they are physical units which are impinged upon continuously by other matter that influences the direction of voltage shifts across the units membranes. It is only the action of a great many neurons, billions in the case of the human nervous system, that intelligent behavior emerges. What is required to understand even the simplest neural system is painstaking analysis, bit by bit, of the architecture and the physiological functioning of its various parts. The biological neural network studied, the vestibular utricular and saccular maculas of the inner ear, are among the most simple of the mammalian neural networks to understand and model. While there is still a long way to go to understand even this most simple neural network in sufficient detail for extrapolation to computers and robots, a start was made. Moreover, the insights obtained and the technologies developed help advance the understanding of the more complex neural networks that underlie human intelligence.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

PubMed

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

Overview of chemical imaging methods to address biological questions.

PubMed

da Cunha, Marcel Menezes Lyra; Trepout, Sylvain; Messaoudi, Cédric; Wu, Ting-Di; Ortega, Richard; Guerquin-Kern, Jean-Luc; Marco, Sergio

2016-05-01

Chemical imaging offers extensive possibilities for better understanding of biological systems by allowing the identification of chemical components at the tissue, cellular, and subcellular levels. In this review, we introduce modern methods for chemical imaging that can be applied to biological samples. This work is mainly addressed to the biological sciences community and includes the bases of different technologies, some examples of its application, as well as an introduction to approaches on combining multimodal data. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Biomedical and Catalytic Opportunities of Virus-Like Particles in Nanotechnology

PubMed Central

Schwarz, B.; Uchida, M.; Douglas, T.

2016-01-01

Within biology, molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nanosystems that exist at the interface of living organisms and nonliving biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. Composed of self-assembling protein subunits, VLPs provide both a model for studying materials’ assembly at the nanoscale and useful building blocks for materials design. The robustness and degree of understanding of many VLP structures allow for the ready use of these systems as versatile nanoparticle platforms for the conjugation of active molecules or as scaffolds for the structural organization of chemical processes. Lastly the prevalence of viruses in all domains of life has led to unique activities of VLPs in biological systems most notably the immune system. Here we discuss recent efforts to apply VLPs in a wide variety of applications with the aim of highlighting how the common structural elements of VLPs have led to their emergence as paradigms for the understanding and design of biological nanomaterials. PMID:28057256

Quantum chemical methods for the investigation of photoinitiated processes in biological systems: theory and applications.

PubMed

Dreuw, Andreas

2006-11-13

With the advent of modern computers and advances in the development of efficient quantum chemical computer codes, the meaningful computation of large molecular systems at a quantum mechanical level became feasible. Recent experimental effort to understand photoinitiated processes in biological systems, for instance photosynthesis or vision, at a molecular level also triggered theoretical investigations in this field. In this Minireview, standard quantum chemical methods are presented that are applicable and recently used for the calculation of excited states of photoinitiated processes in biological molecular systems. These methods comprise configuration interaction singles, the complete active space self-consistent field method, and time-dependent density functional theory and its variants. Semiempirical approaches are also covered. Their basic theoretical concepts and mathematical equations are briefly outlined, and their properties and limitations are discussed. Recent successful applications of the methods to photoinitiated processes in biological systems are described and theoretical tools for the analysis of excited states are presented.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

PubMed

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

[Biological therapies in systemic lupus erythematosus].

PubMed

Cairoli, Ernesto; Espinosa, Gerard; Cervera, Ricard

2010-07-01

The immunosuppressive agents used in patients with systemic lupus erythematosus (SLE) have significantly improved prognosis. However, it is necessary to develop more specific immunosuppressive treatments with less toxicity. Better understanding of the mechanisms involved in the loss of tolerance in autoimmune diseases has contributed to the development of potential new treatments called biologic therapies. The targets of these biological therapies are directed toward the B cell depletion, interference in the co-stimulation signals and the blockade of cytokines. Therapies using anti-CD20 monoclonal antibodies have shown satisfactory results especially in patients with SLE refractory to conventional treatment. The biological therapies provide encouraging results that represent a possible option in the treatment of refractory patients as well as a potential therapy in the future management of SLE.

Mapping Proteome-Wide Interactions of Reactive Chemicals Using Chemoproteomic Platforms

PubMed Central

Counihan, Jessica L.; Ford, Breanna; Nomura, Daniel K.

2015-01-01

A large number of pharmaceuticals, endogenous metabolites, and environmental chemicals act through covalent mechanisms with protein targets. Yet, their specific interactions with the proteome still remain poorly defined for most of these reactive chemicals. Deciphering direct protein targets of reactive small-molecules is critical in understanding their biological action, off-target effects, potential toxicological liabilities, and development of safer and more selective agents. Chemoproteomic technologies have arisen as a powerful strategy that enable the assessment of proteome-wide interactions of these irreversible agents directly in complex biological systems. We review here several chemoproteomic strategies that have facilitated our understanding of specific protein interactions of irreversibly-acting pharmaceuticals, endogenous metabolites, and environmental electrophiles to reveal novel pharmacological, biological, and toxicological mechanisms. PMID:26647369

A systems biology analysis of autophagy in cancer therapy.

PubMed

Shi, Zheng; Li, Chun-yang; Zhao, Si; Yu, Yang; An, Na; Liu, Yong-xi; Wu, Chuan-fang; Yue, Bi-song; Bao, Jin-ku

2013-09-01

Autophagy, which degrades redundant or damaged cellular constituents, is intricately relevant to a variety of human diseases, most notably cancer. Autophagy exerts distinct effects on cancer initiation and progression, due to the intrinsic overlapping of autophagic and cancer signalling pathways. However, due to the complexity of cancer as a systemic disease, the fate of cancer cells is not decided by any one signalling pathway. Numerous autophagic inter-connectivity and cross-talk pathways need to be further clarified at a systems level. In this review, we propose a systems biology perspective for the comprehensive analysis of the autophagy-cancer network, focusing on systems biology analysis in autophagy and cancer therapy. Together, these analyses may not only improve our understanding on autophagy-cancer relationships, but also facilitate cancer drug discovery. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Preferential edge habitat colonization by a specialist weevil, Rhinoncomimus latipes (Coleoptera: Curculionidae)

Treesearch

J.A. Hough-Goldstein; E. Lake; V. D' Amico; S.H. Berg

2012-01-01

Understanding the behavioral basis of dispersal and colonization is critical in biological control systems, where success of a natural enemy depends in part on its ability to find and move to new host patches. We studied behavior of the specialist weevil Rhinoncomimus latipes Korotyaev, a biological control agent of mile-a-minute weed, ...

Developing a large-scale model to predict the effects of land use and climatic variation on the biological condition of USA streams and rivers

EPA Science Inventory

The US EPA’s National Rivers and Streams Assessment (NRSA) uses spatially balanced sampling to estimate the proportion of streams within the continental US (CONUS) that fail to support healthy biological communities. However, to manage these systems, we also must understand...

An overview of bioinformatics methods for modeling biological pathways in yeast

PubMed Central

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao

2016-01-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein–protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae. In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways in S. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. PMID:26476430

Learning immunology from the yellow fever vaccine: innate immunity to systems vaccinology.

PubMed

Pulendran, Bali

2009-10-01

Despite their great success, we understand little about how effective vaccines stimulate protective immune responses. Two recent developments promise to yield such understanding: the appreciation of the crucial role of the innate immune system in sensing microorganisms and tuning immune responses, and advances in systems biology. Here I review how these developments are yielding insights into the mechanism of action of the yellow fever vaccine, one of the most successful vaccines ever developed, and the broader implications for vaccinology.

Convolving engineering and medical pedagogies for training of tomorrow's health care professionals.

PubMed

Lee, Raphael C

2013-03-01

Several fundamental benefits justify why biomedical engineering and medicine should form a more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers. Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the era of molecular biology well into today's era of molecular systems biology, which focuses on understanding the rules that govern the behavior of complex living systems. This has important medical implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in molecular systems biology to higher levels of biological organization (organ, system, and organismal levels) and then to develop new medical therapeutics based on simulation and medical informatics analysis. Higher education in biological and medical sciences must adapt to a new set of training objectives. This will involve a shifting away from reductionist problem solving toward more integrative, continuum, and predictive modeling approaches which traditionally have been more associated with engineering science. Future biomedical engineers and MDs must be able to predict clinical response to therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing rules of complex system behavior and skill sets in manipulating these systems to achieve a practical desired outcome are taught. Similarly, graduate biomedical engineering programs will include more practical exposure to clinical problem solving.

Integrating evo-devo with ecology for a better understanding of phenotypic evolution

PubMed Central

Emília Santos, M.; Berger, Chloé S.; Refki, Peter N.

2015-01-01

Evolutionary developmental biology (evo-devo) has provided invaluable contributions to our understanding of the mechanistic relationship between genotypic and phenotypic change. Similarly, evolutionary ecology has greatly advanced our understanding of the relationship between the phenotype and the environment. To fully understand the evolution of organismal diversity, a thorough integration of these two fields is required. This integration remains highly challenging because model systems offering a rich ecological and evolutionary background, together with the availability of developmental genetic tools and genomic resources, are scarce. In this review, we introduce the semi-aquatic bugs (Gerromorpha, Heteroptera) as original models well suited to study why and how organisms diversify. The Gerromorpha invaded water surfaces over 200 mya and diversified into a range of remarkable new forms within this new ecological habitat. We summarize the biology and evolutionary history of this group of insects and highlight a set of characters associated with the habitat change and the diversification that followed. We further discuss the morphological, behavioral, molecular and genomic tools available that together make semi-aquatic bugs a prime model for integration across disciplines. We present case studies showing how the implementation and combination of these approaches can advance our understanding of how the interaction between genotypes, phenotypes and the environment drives the evolution of distinct morphologies. Finally, we explain how the same set of experimental designs can be applied in other systems to address similar biological questions. PMID:25750411

Integrating evo-devo with ecology for a better understanding of phenotypic evolution.

PubMed

Santos, M Emília; Berger, Chloé S; Refki, Peter N; Khila, Abderrahman

2015-11-01

Evolutionary developmental biology (evo-devo) has provided invaluable contributions to our understanding of the mechanistic relationship between genotypic and phenotypic change. Similarly, evolutionary ecology has greatly advanced our understanding of the relationship between the phenotype and the environment. To fully understand the evolution of organismal diversity, a thorough integration of these two fields is required. This integration remains highly challenging because model systems offering a rich ecological and evolutionary background, together with the availability of developmental genetic tools and genomic resources, are scarce. In this review, we introduce the semi-aquatic bugs (Gerromorpha, Heteroptera) as original models well suited to study why and how organisms diversify. The Gerromorpha invaded water surfaces over 200 mya and diversified into a range of remarkable new forms within this new ecological habitat. We summarize the biology and evolutionary history of this group of insects and highlight a set of characters associated with the habitat change and the diversification that followed. We further discuss the morphological, behavioral, molecular and genomic tools available that together make semi-aquatic bugs a prime model for integration across disciplines. We present case studies showing how the implementation and combination of these approaches can advance our understanding of how the interaction between genotypes, phenotypes and the environment drives the evolution of distinct morphologies. Finally, we explain how the same set of experimental designs can be applied in other systems to address similar biological questions. © The Author 2015. Published by Oxford University Press.

Visualising associations between paired ‘omics’ data sets

PubMed Central

2012-01-01

Background Each omics platform is now able to generate a large amount of data. Genomics, proteomics, metabolomics, interactomics are compiled at an ever increasing pace and now form a core part of the fundamental systems biology framework. Recently, several integrative approaches have been proposed to extract meaningful information. However, these approaches lack of visualisation outputs to fully unravel the complex associations between different biological entities. Results The multivariate statistical approaches ‘regularized Canonical Correlation Analysis’ and ‘sparse Partial Least Squares regression’ were recently developed to integrate two types of highly dimensional ‘omics’ data and to select relevant information. Using the results of these methods, we propose to revisit few graphical outputs to better understand the relationships between two ‘omics’ data and to better visualise the correlation structure between the different biological entities. These graphical outputs include Correlation Circle plots, Relevance Networks and Clustered Image Maps. We demonstrate the usefulness of such graphical outputs on several biological data sets and further assess their biological relevance using gene ontology analysis. Conclusions Such graphical outputs are undoubtedly useful to aid the interpretation of these promising integrative analysis tools and will certainly help in addressing fundamental biological questions and understanding systems as a whole. Availability The graphical tools described in this paper are implemented in the freely available R package mixOmics and in its associated web application. PMID:23148523

Transient Resetting: A Novel Mechanism for Synchrony and Its Biological Examples

PubMed Central

Li, Chunguang; Chen, Luonan; Aihara, Kazuyuki

2006-01-01

The study of synchronization in biological systems is essential for the understanding of the rhythmic phenomena of living organisms at both molecular and cellular levels. In this paper, by using simple dynamical systems theory, we present a novel mechanism, named transient resetting, for the synchronization of uncoupled biological oscillators with stimuli. This mechanism not only can unify and extend many existing results on (deterministic and stochastic) stimulus-induced synchrony, but also may actually play an important role in biological rhythms. We argue that transient resetting is a possible mechanism for the synchronization in many biological organisms, which might also be further used in the medical therapy of rhythmic disorders. Examples of the synchronization of neural and circadian oscillators as well as a chaotic neuron model are presented to verify our hypothesis. PMID:16933980

Linking Insects with Crustacea: Physiology of the Pancrustacea: An Introduction to the Symposium.

PubMed

Tamone, Sherry L; Harrison, Jon F

2015-11-01

Insects and crustaceans represent critical, dominant animal groups (by biomass and species number) in terrestrial and aquatic systems, respectively. Insects (hexapods) and crustaceans are historically grouped under separate taxonomic classes within the Phylum Arthropoda, and the research communities studying hexapods and crustaceans are quite distinct. More recently, the hexapods have been shown to be evolutionarily derived from basal crustaceans, and the clade Pancrustacea recognizes this relationship. This recent evolutionary perspective, and the fact that the Society for Integrative and Comparative Biology has strong communities in both invertebrate biology and insect physiology, provides the motivation for this symposium. Speakers in this symposium were selected because of their expertise in a particular field of insect or crustacean physiology, and paired in such a way as to provide a comparative view of the state of the current research in their respective fields. Presenters discussed what aspects of the physiological system are clearly conserved across insects and crustaceans and how cross-talk between researchers utilizing insects and crustaceans can fertilize understanding of such conserved systems. Speakers were also asked to identify strategies that would enable improved understanding of the evolution of physiological systems of the terrestrial insects from the aquatic crustaceans. The following collection of articles describes multiple recent advances in our understanding of Pancrustacean physiology. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

The Hydra model - a model for what?

PubMed

Gierer, Alfred

2012-01-01

The introductory personal remarks refer to my motivations for choosing research projects, and for moving from physics to molecular biology and then to development, with Hydra as a model system. Historically, Trembley's discovery of Hydra regeneration in 1744 was the beginning of developmental biology as we understand it, with passionate debates about preformation versus de novo generation, mechanisms versus organisms. In fact, seemingly conflicting bottom-up and top-down concepts are both required in combination to understand development. In modern terms, this means analysing the molecules involved, as well as searching for physical principles underlying development within systems of molecules, cells and tissues. During the last decade, molecular biology has provided surprising and impressive evidence that the same types of molecules and molecular systems are involved in pattern formation in a wide range of organisms, including coelenterates like Hydra, and thus appear to have been "invented" early in evolution. Likewise, the features of certain systems, especially those of developmental regulation, are found in many different organisms. This includes the generation of spatial structures by the interplay of self-enhancing activation and "lateral" inhibitory effects of wider range, which is a main topic of my essay. Hydra regeneration is a particularly clear model for the formation of defined patterns within initially near-uniform tissues. In conclusion, this essay emphasizes the analysis of development in terms of physical laws, including the application of mathematics, and insists that Hydra was, and will continue to be, a rewarding model for understanding general features of embryogenesis and regeneration.

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

Suppression of single-wall carbon nanotube redox reaction by adsorbed proteins

NASA Astrophysics Data System (ADS)

Nakayama, Tomohito; Tanaka, Takeshi; Shiraki, Kentaro; Hase, Muneaki; Hirano, Atsushi

2018-07-01

Single-wall carbon nanotubes (SWCNTs) are widely used in biological applications. In biological systems, proteins readily adsorb to SWCNTs. However, little is known about the effects of proteins on the physicochemical properties of SWCNTs, such as their redox reaction. In this study, we measured the absorption and Raman spectra of SWCNTs dispersed in the presence of proteins such as bovine serum albumin to observe the redox reaction of the protein-adsorbed SWCNTs. The adsorbed proteins suppressed the redox reaction by forming thick and dense layers around the SWCNTs. Our findings are useful for understanding the behaviors of SWCNTs in biological systems.

Biological Networks for Cancer Candidate Biomarkers Discovery

PubMed Central

Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

2016-01-01

Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. PMID:27625573

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

PubMed

Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

2009-10-15

Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich--data poor' paradox in Systems Biology.

Systems biology and the quest for correlates of protection to guide the development of an HIV vaccine.

PubMed

Kuri-Cervantes, Leticia; Fourati, Slim; Canderan, Glenda; Sekaly, Rafick-Pierre

2016-08-01

Over the last three decades, a myriad of data has been generated regarding HIV/SIV evolution, immune evasion, immune response, and pathogenesis. Much of this data can be integrated and potentially used to generate a successful vaccine. Although individual approaches have begun to shed light on mechanisms involved in vaccine-conferred protection from infection, true correlates of protection have not yet been identified. The systems biology approach helps unify datasets generated using different techniques and broaden our understanding of HIV immunopathogenesis. Moreover, systems biology is a tool that can provide correlates of protection, which can be targeted for the production of a successful HIV vaccine. Copyright © 2016. Published by Elsevier Ltd.

The Gas6/TAM System and Multiple Sclerosis.

PubMed

Bellan, Mattia; Pirisi, Mario; Sainaghi, Pier Paolo

2016-10-28

Growth arrest specific 6 (Gas6) is a multimodular circulating protein, the biological actions of which are mediated by the interaction with three transmembrane tyrosine kinase receptors: Tyro3, Axl, and MerTK, collectively named TAM. Over the last few decades, many progresses have been done in the understanding of the biological activities of this highly pleiotropic system, which plays a role in the regulation of immune response, inflammation, coagulation, cell growth, and clearance of apoptotic bodies. Recent findings have further related Gas6 and TAM receptors to neuroinflammation in general and, specifically, to multiple sclerosis (MS). In this paper, we review the biology of the Gas6/TAM system and the current evidence supporting its potential role in the pathogenesis of MS.

Mirror Neurons and the Evolution of Language

ERIC Educational Resources Information Center

Corballis, Michael C.

2010-01-01

The mirror system provided a natural platform for the subsequent evolution of language. In nonhuman primates, the system provides for the understanding of biological action, and possibly for imitation, both prerequisites for language. I argue that language evolved from manual gestures, initially as a system of pantomime, but with gestures…

From the Field to the Classroom: Developing Scientifically Literate Citizens Using the Understanding Global Change Framework in Education and Citizen Science

NASA Astrophysics Data System (ADS)

Toupin, C.; Bean, J. R.; Gavenus, K.; Johnson, H.; Toupin, S.

2017-12-01

With the copious amount of science and pseudoscience reported on by non-experts in the media, it is critical for educators to help students develop into scientifically literate citizens. One of the most direct ways to help students develop deep scientific understanding and the skills to critically question the information they encounter is to bring science into their daily experiences and to contextualize scientific inquiry within the classroom. Our work aims to use a systems-based models approach to engage students in science, in both formal and informal contexts. Using the Understanding Global Change (UGC) and the Understanding Science models developed at the Museum of Paleontology at UC Berkeley, high school students from Arizona were tasked with developing a viable citizen science program for use at the Center for Alaskan Coastal Studies in Homer, Alaska. Experts used the UGC model to help students define why they were doing the work, and give context to the importance of citizen science. Empowered with an understanding of the scientific process, excited by the purpose of their work and how it could contribute to the scientific community, students whole-heartedly worked together to develop intertidal monitoring protocols for two locations while staying at Peterson Bay Field Station, Homer. Students, instructors, and scientists used system models to communicate and discuss their understanding of the biological, physical, and chemical processes in Kachemak Bay. This systems-based models approach is also being used in an integrative high school physics, chemistry, and biology curriculum in a truly unprecedented manner. Using the Understanding Global Change framework to organize curriculum scope and sequence, the course addresses how the earth systems work, how interdisciplinary science knowledge is necessary to understand those systems, and how scientists and students can measure changes within those systems.

Lunar Plant Biology - A Review of the Apollo Era

NASA Astrophysics Data System (ADS)

Ferl, Robert J.; Paul, Anna-Lisa

2010-04-01

Recent plans for human return to the Moon have significantly elevated scientific interest in the lunar environment with emphasis on the science to be done in preparation for the return and while on the lunar surface. Since the return to the Moon is envisioned as a dedicated and potentially longer-term commitment to lunar exploration, questions of the lunar environment and particularly its impact on biology and biological systems have become a significant part of the lunar science discussion. Plants are integral to the discussion of biology on the Moon. Plants are envisioned as important components of advanced habitats and fundamental components of advanced life-support systems. Moreover, plants are sophisticated multicellular eukaryotic life-forms with highly orchestrated developmental processes, well-characterized signal transduction pathways, and exceedingly fine-tuned responses to their environments. Therefore, plants represent key test organisms for understanding the biological impact of the lunar environment on terrestrial life-forms. Indeed, plants were among the initial and primary organisms that were exposed to returned lunar regolith from the Apollo lunar missions. This review discusses the original experiments involving plants in association with the Apollo samples, with the intent of understanding those studies within the context of the first lunar exploration program and drawing from those experiments the data to inform the studies critical within the next lunar exploration science agenda.

Lunar plant biology--a review of the Apollo era.

PubMed

Ferl, Robert J; Paul, Anna-Lisa

2010-04-01

Recent plans for human return to the Moon have significantly elevated scientific interest in the lunar environment with emphasis on the science to be done in preparation for the return and while on the lunar surface. Since the return to the Moon is envisioned as a dedicated and potentially longer-term commitment to lunar exploration, questions of the lunar environment and particularly its impact on biology and biological systems have become a significant part of the lunar science discussion. Plants are integral to the discussion of biology on the Moon. Plants are envisioned as important components of advanced habitats and fundamental components of advanced life-support systems. Moreover, plants are sophisticated multicellular eukaryotic life-forms with highly orchestrated developmental processes, well-characterized signal transduction pathways, and exceedingly fine-tuned responses to their environments. Therefore, plants represent key test organisms for understanding the biological impact of the lunar environment on terrestrial life-forms. Indeed, plants were among the initial and primary organisms that were exposed to returned lunar regolith from the Apollo lunar missions. This review discusses the original experiments involving plants in association with the Apollo samples, with the intent of understanding those studies within the context of the first lunar exploration program and drawing from those experiments the data to inform the studies critical within the next lunar exploration science agenda.

The cell biology of Tobacco mosaic virus replication and movement

PubMed Central

Liu, Chengke; Nelson, Richard S.

2013-01-01

Successful systemic infection of a plant by Tobacco mosaic virus (TMV) requires three processes that repeat over time: initial establishment and accumulation in invaded cells, intercellular movement, and systemic transport. Accumulation and intercellular movement of TMV necessarily involves intracellular transport by complexes containing virus and host proteins and virus RNA during a dynamic process that can be visualized. Multiple membranes appear to assist TMV accumulation, while membranes, microfilaments and microtubules appear to assist TMV movement. Here we review cell biological studies that describe TMV-membrane, -cytoskeleton, and -other host protein interactions which influence virus accumulation and movement in leaves and callus tissue. The importance of understanding the developmental phase of the infection in relationship to the observed virus-membrane or -host protein interaction is emphasized. Utilizing the latest observations of TMV-membrane and -host protein interactions within our evolving understanding of the infection ontogeny, a model for TMV accumulation and intracellular spread in a cell biological context is provided. PMID:23403525

Results from a Pilot Study of a Curriculum Unit Designed to Help Middle School Students Understand Chemical Reactions in Living Systems

ERIC Educational Resources Information Center

Herrmann-Abell, Cari F.; Flanagan, Jean C.; Roseman, Jo Ellen

2012-01-01

Students often have trouble understanding key biology ideas because they lack an understanding of foundational chemistry ideas. AAAS Project 2061 is collaborating with BSCS in the development a curriculum unit that connects core chemistry and biochemistry ideas in order to help eighth grade students build the conceptual foundation needed for high…

Data-intensive drug development in the information age: applications of Systems Biology/Pharmacology/Toxicology.

PubMed

Kiyosawa, Naoki; Manabe, Sunao

2016-01-01

Pharmaceutical companies continuously face challenges to deliver new drugs with true medical value. R&D productivity of drug development projects depends on 1) the value of the drug concept and 2) data and in-depth knowledge that are used rationally to evaluate the drug concept's validity. A model-based data-intensive drug development approach is a key competitive factor used by innovative pharmaceutical companies to reduce information bias and rationally demonstrate the value of drug concepts. Owing to the accumulation of publicly available biomedical information, our understanding of the pathophysiological mechanisms of diseases has developed considerably; it is the basis for identifying the right drug target and creating a drug concept with true medical value. Our understanding of the pathophysiological mechanisms of disease animal models can also be improved; it can thus support rational extrapolation of animal experiment results to clinical settings. The Systems Biology approach, which leverages publicly available transcriptome data, is useful for these purposes. Furthermore, applying Systems Pharmacology enables dynamic simulation of drug responses, from which key research questions to be addressed in the subsequent studies can be adequately informed. Application of Systems Biology/Pharmacology to toxicology research, namely Systems Toxicology, should considerably improve the predictability of drug-induced toxicities in clinical situations that are difficult to predict from conventional preclinical toxicology studies. Systems Biology/Pharmacology/Toxicology models can be continuously improved using iterative learn-confirm processes throughout preclinical and clinical drug discovery and development processes. Successful implementation of data-intensive drug development approaches requires cultivation of an adequate R&D culture to appreciate this approach.

Introductory physics in biological context: An approach to improve introductory physics for life science students

NASA Astrophysics Data System (ADS)

Crouch, Catherine H.; Heller, Kenneth

2014-05-01

We describe restructuring the introductory physics for life science students (IPLS) course to better support these students in using physics to understand their chosen fields. Our courses teach physics using biologically rich contexts. Specifically, we use examples in which fundamental physics contributes significantly to understanding a biological system to make explicit the value of physics to the life sciences. This requires selecting the course content to reflect the topics most relevant to biology while maintaining the fundamental disciplinary structure of physics. In addition to stressing the importance of the fundamental principles of physics, an important goal is developing students' quantitative and problem solving skills. Our guiding pedagogical framework is the cognitive apprenticeship model, in which learning occurs most effectively when students can articulate why what they are learning matters to them. In this article, we describe our courses, summarize initial assessment data, and identify needs for future research.

The -omics Era- Toward a Systems-Level Understanding of Streptomyces

PubMed Central

Zhou, Zhan; Gu, Jianying; Du, Yi-Ling; Li, Yong-Quan; Wang, Yufeng

2011-01-01

Streptomyces is a group of soil bacteria of medicinal, economic, ecological, and industrial importance. It is renowned for its complex biology in gene regulation, antibiotic production, morphological differentiation, and stress response. In this review, we provide an overview of the recent advances in Streptomyces biology inspired by -omics based high throughput technologies. In this post-genomic era, vast amounts of data have been integrated to provide significant new insights into the fundamental mechanisms of system control and regulation dynamics of Streptomyces. PMID:22379394

Rigid Biological Systems as Models for Synthetic Composites

NASA Astrophysics Data System (ADS)

Mayer, George

2005-11-01

Advances that have been made in understanding the mechanisms underlying the mechanical behavior of a number of biological materials (namely mollusk shells and sponge spicules) are discussed here. Attempts at biomimicry of the structure of a nacreous layer of a mollusk shell have shown reasonable success. However, they have revealed additional issues that must be addressed if new synthetic composite materials that are based on natural systems are to be constructed. Some of the important advantages and limitations of copying from nature are also described here.

Diagnostic of students' misconceptions using the Biological Concepts Instrument (BCI): A method for conducting an educational needs assessment

PubMed Central

Champagne Queloz, Annie; Klymkowsky, Michael W.; Stern, Elsbeth; Hafen, Ernst; Köhler, Katja

2017-01-01

Concept inventories, constructed based on an analysis of students’ thinking and their explanations of scientific situations, serve as diagnostics for identifying misconceptions and logical inconsistencies and provide data that can help direct curricular reforms. In the current project, we distributed the Biological Concepts Instrument (BCI) to 17-18-year-old students attending the highest track of the Swiss school system (Gymnasium). Students’ performances on many questions related to evolution, genetics, molecular properties and functions were diverse. Important common misunderstandings were identified in the areas of evolutionary processes, molecular properties and an appreciation of stochastic processes in biological systems. Our observations provide further evidence that the BCI is efficient in identifying specific areas where targeted instruction is required. Based on these observations we have initiated changes at several levels to reconsider how biological systems are presented to university biology studies with the goal of improving student’s foundational understanding. PMID:28493960

A research project-based and self-determined teaching system of molecular biology techniques for undergraduates.

PubMed

Zhang, Shuping

2008-05-01

Molecular biology techniques play a very important role in understanding the biological activity. Students who major in biology should know not only how to perform experiments, but also the reasons for performing them. Having the concept of conducting research by integrating various techniques is especially important. This paper introduces a research project-based and self-determined teaching system of molecular biology techniques for undergraduates. Its aim is to create an environment mimicking real research programs and to help students build up confidence in their research skills. The students are allowed to explore a set of commonly used molecular biology techniques to solve some fundamental problems about genes on their own. They find a gene of interest, write a mini-proposal, and give an oral presentation. This course provides students a foundation before entering the research laboratory and allows them to adapt easily to real research programs. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

Advances in Structural Biology and the Application to Biological Filament Systems.

PubMed

Popp, David; Koh, Fujiet; Scipion, Clement P M; Ghoshdastider, Umesh; Narita, Akihiro; Holmes, Kenneth C; Robinson, Robert C

2018-04-01

Structural biology has experienced several transformative technological advances in recent years. These include: development of extremely bright X-ray sources (microfocus synchrotron beamlines and free electron lasers) and the use of electrons to extend protein crystallography to ever decreasing crystal sizes; and an increase in the resolution attainable by cryo-electron microscopy. Here we discuss the use of these techniques in general terms and highlight their application for biological filament systems, an area that is severely underrepresented in atomic resolution structures. We assemble a model of a capped tropomyosin-actin minifilament to demonstrate the utility of combining structures determined by different techniques. Finally, we survey the methods that attempt to transform high resolution structural biology into more physiological environments, such as the cell. Together these techniques promise a compelling decade for structural biology and, more importantly, they will provide exciting discoveries in understanding the designs and purposes of biological machines. © 2018 The Authors. BioEssays Published by WILEY Periodicals, Inc.

Model-based design of experiments for cellular processes.

PubMed

Chakrabarty, Ankush; Buzzard, Gregery T; Rundell, Ann E

2013-01-01

Model-based design of experiments (MBDOE) assists in the planning of highly effective and efficient experiments. Although the foundations of this field are well-established, the application of these techniques to understand cellular processes is a fertile and rapidly advancing area as the community seeks to understand ever more complex cellular processes and systems. This review discusses the MBDOE paradigm along with applications and challenges within the context of cellular processes and systems. It also provides a brief tutorial on Fisher information matrix (FIM)-based and Bayesian experiment design methods along with an overview of existing software packages and computational advances that support MBDOE application and adoption within the Systems Biology community. As cell-based products and biologics progress into the commercial sector, it is anticipated that MBDOE will become an essential practice for design, quality control, and production. Copyright © 2013 Wiley Periodicals, Inc.

Understanding force-generating microtubule systems through in vitro reconstitution

PubMed Central

Kok, Maurits; Dogterom, Marileen

2016-01-01

ABSTRACT Microtubules switch between growing and shrinking states, a feature known as dynamic instability. The biochemical parameters underlying dynamic instability are modulated by a wide variety of microtubule-associated proteins that enable the strict control of microtubule dynamics in cells. The forces generated by controlled growth and shrinkage of microtubules drive a large range of processes, including organelle positioning, mitotic spindle assembly, and chromosome segregation. In the past decade, our understanding of microtubule dynamics and microtubule force generation has progressed significantly. Here, we review the microtubule-intrinsic process of dynamic instability, the effect of external factors on this process, and how the resulting forces act on various biological systems. Recently, reconstitution-based approaches have strongly benefited from extensive biochemical and biophysical characterization of individual components that are involved in regulating or transmitting microtubule-driven forces. We will focus on the current state of reconstituting increasingly complex biological systems and provide new directions for future developments. PMID:27715396

Spoken language achieves robustness and evolvability by exploiting degeneracy and neutrality.

PubMed

Winter, Bodo

2014-10-01

As with biological systems, spoken languages are strikingly robust against perturbations. This paper shows that languages achieve robustness in a way that is highly similar to many biological systems. For example, speech sounds are encoded via multiple acoustically diverse, temporally distributed and functionally redundant cues, characteristics that bear similarities to what biologists call "degeneracy". Speech is furthermore adequately characterized by neutrality, with many different tongue configurations leading to similar acoustic outputs, and different acoustic variants understood as the same by recipients. This highlights the presence of a large neutral network of acoustic neighbors for every speech sound. Such neutrality ensures that a steady backdrop of variation can be maintained without impeding communication, assuring that there is "fodder" for subsequent evolution. Thus, studying linguistic robustness is not only important for understanding how linguistic systems maintain their functioning upon the background of noise, but also for understanding the preconditions for language evolution. © 2014 WILEY Periodicals, Inc.

Social Determinants of Population Health: A Systems Sciences Approach

PubMed Central

Fink, David S.; Keyes, Katherine M.; Cerdá, Magdalena

2016-01-01

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective. PMID:27642548

Constructive biology and approaches to temporal grounding in postreactive robotics

NASA Astrophysics Data System (ADS)

Nehaniv, Chrystopher L.; Dautenhahn, Kerstin; Loomes, Martin J.

1999-08-01

Constructive Biology means understanding biological mechanisms through building systems that exhibit life-like properties. Applications include learning engineering tricks from biological system, as well as the validation in biological modeling. In particular, biological system in the course of development and experience become temporally grounded. Researchers attempting to transcend mere reactivity have been inspired by the drives, motivations, homeostasis, hormonal control, and emotions of animals. In order to contextualize and modulate behavior, these ideas have been introduced into robotics and synthetic agents, while further flexibility is achieved by introducing learning. Broadening scope of the temporal horizon further requires post-reactive techniques that address not only the action in the now, although such action may perhaps be modulated by drives and affect. Support is needed for expressing and benefitting from pats experiences, predictions of the future, and form interaction histories of the self with the world and with other agents. Mathematical methods provide a new way to support such grounding in the construction of post-reactive systems. Moreover, the communication of such mathematical encoded histories of experience between situated agents opens a route to narrative intelligence, analogous to communication or story telling in societies.

Auditory Power-Law Activation Avalanches Exhibit a Fundamental Computational Ground State

NASA Astrophysics Data System (ADS)

Stoop, Ruedi; Gomez, Florian

2016-07-01

The cochlea provides a biological information-processing paradigm that we are only beginning to understand in its full complexity. Our work reveals an interacting network of strongly nonlinear dynamical nodes, on which even a simple sound input triggers subnetworks of activated elements that follow power-law size statistics ("avalanches"). From dynamical systems theory, power-law size distributions relate to a fundamental ground state of biological information processing. Learning destroys these power laws. These results strongly modify the models of mammalian sound processing and provide a novel methodological perspective for understanding how the brain processes information.

Systems immunology: just getting started.

PubMed

Davis, Mark M; Tato, Cristina M; Furman, David

2017-06-20

Systems-biology approaches in immunology take various forms, but here we review strategies for measuring a broad swath of immunological functions as a means of discovering previously unknown relationships and phenomena and as a powerful way of understanding the immune system as a whole. This approach has rejuvenated the field of vaccine development and has fostered hope that new ways will be found to combat infectious diseases that have proven refractory to classical approaches. Systems immunology also presents an important new strategy for understanding human immunity directly, taking advantage of the many ways the immune system of humans can be manipulated.

Systems immunology: just getting started

PubMed Central

Davis, Mark M; Tato, Cristina M; Furman, David

2018-01-01

Systems-biology approaches in immunology take various forms, but here we review strategies for measuring a broad swath of immunological functions as a means of discovering previously unknown relationships and phenomena and as a powerful way of understanding the immune system as a whole. This approach has rejuvenated the field of vaccine development and has fostered hope that new ways will be found to combat infectious diseases that have proven refractory to classical approaches. Systems immunology also presents an important new strategy for understanding human immunity directly, taking advantage of the many ways the immune system of humans can be manipulated. PMID:28632713

Cellular processing and destinies of artificial DNA nanostructures.

PubMed

Lee, Di Sheng; Qian, Hang; Tay, Chor Yong; Leong, David Tai

2016-08-07

Since many bionanotechnologies are targeted at cells, understanding how and where their interactions occur and the subsequent results of these interactions is important. Changing the intrinsic properties of DNA nanostructures and linking them with interactions presents a holistic and powerful strategy for understanding dual nanostructure-biological systems. With the recent advances in DNA nanotechnology, DNA nanostructures present a great opportunity to understand the often convoluted mass of information pertaining to nanoparticle-biological interactions due to the more precise control over their chemistry, sizes, and shapes. Coupling just some of these designs with an understanding of biological processes is both a challenge and a source of opportunities. Despite continuous advances in the field of DNA nanotechnology, the intracellular fate of DNA nanostructures has remained unclear and controversial. Because understanding its cellular processing and destiny is a necessary prelude to any rational design of exciting and innovative bionanotechnology, in this review, we will discuss and provide a comprehensive picture relevant to the intracellular processing and the fate of various DNA nanostructures which have been remained elusive for some time. We will also link the unique capabilities of DNA to some novel ideas for developing next-generation bionanotechnologies.

Systems biology of lactic acid bacteria: a critical review

PubMed Central

2011-01-01

Understanding the properties of a system as emerging from the interaction of well described parts is the most important goal of Systems Biology. Although in the practice of Lactic Acid Bacteria (LAB) physiology we most often think of the parts as the proteins and metabolites, a wider interpretation of what a part is can be useful. For example, different strains or species can be the parts of a community, or we could study only the chemical reactions as the parts of metabolism (and forgetting about the enzymes that catalyze them), as is done in flux balance analysis. As long as we have some understanding of the properties of these parts, we can investigate whether their interaction leads to novel or unanticipated behaviour of the system that they constitute. There has been a tendency in the Systems Biology community to think that the collection and integration of data should continue ad infinitum, or that we will otherwise not be able to understand the systems that we study in their details. However, it may sometimes be useful to take a step back and consider whether the knowledge that we already have may not explain the system behaviour that we find so intriguing. Reasoning about systems can be difficult, and may require the application of mathematical techniques. The reward is sometimes the realization of unexpected conclusions, or in the worst case, that we still do not know enough details of the parts, or of the interactions between them. We will discuss a number of cases, with a focus on LAB-related work, where a typical systems approach has brought new knowledge or perspective, often counterintuitive, and clashing with conclusions from simpler approaches. Also novel types of testable hypotheses may be generated by the systems approach, which we will illustrate. Finally we will give an outlook on the fields of research where the systems approach may point the way for the near future. PMID:21995498

Toward an Understanding of the Epistemic Values of Biological Scientists as Expressed in Scholarly Publication

ERIC Educational Resources Information Center

Dunn, Kathel

2010-01-01

This dissertation develops a deeper understanding of the epistemic values of scientists, specifically exploring the proposed values of community, collaboration, connectivity and credit as part of the scholarly communication system. These values are the essence of scientists actively engaged in conducting science and in communicating their work to…

Student Understanding of Water and Water Resources: A Review of the Literature.

ERIC Educational Resources Information Center

Brody, Michael J.

This paper reviews the educational research related to student understanding of water and water resources. The literature is drawn primarily from science and environmental education literature and is divided into student knowledge of: physical and chemical properties, biology, earth systems and water resources. The majority of work has been in the…

Increasing algal photosynthetic productivity by integrating ecophysiology with systems biology.

PubMed

Peers, Graham

2014-11-01

Oxygenic photosynthesis is the process by which plants, algae, and cyanobacteria convert sunlight and CO2 into chemical energy and biomass. Previously published estimates suggest that algal photosynthesis is, at best, able to convert approximately 5-7% of incident light energy to biomass and there is opportunity for improvement. Recent analyses of in situ photophysiology in mass cultures of algae and cyanobacteria show that cultivation methods can have detrimental effects on a cell's photophysiology - reinforcing the need to understand the complex responses of cell biology to a highly variable environment. A systems-based approach to understanding the stresses and efficiencies associated with light-energy harvesting, CO2 fixation, and carbon partitioning will be necessary to make major headway toward improving photosynthetic yields. Copyright © 2014 Elsevier Ltd. All rights reserved.

New translational perspectives for blood-based biomarkers of PTSD: From glucocorticoid to immune mediators of stress susceptibility

PubMed Central

Daskalakis, Nikolaos P.; Cohen, Hagit; Nievergelt, Caroline M.; Baker, Dewleen G.; Buxbaum, Joseph D.; Russo, Scott J.; Yehuda, Rachel

2016-01-01

Although biological systems have evolved to promote stress-resilience, there is variation in stress-responses. Understanding the biological basis of such individual differences has implications for understanding Posttraumatic Stress Disorder (PTSD) etiology, which is a maladaptive response to trauma occurring only in a subset of vulnerable individuals. PTSD involves failure to reinstate physiological homeostasis after traumatic events and is due to either intrinsic or trauma-related alterations in physiological systems across the body. Master homeostatic regulators that circulate and operate throughout the organism, such as stress hormones (e.g., glucocorticoids) and immune mediators (e.g., cytokines), are at the crossroads of peripheral and central susceptibility pathways and represent promising functional biomarkers of stress-response and target for novel therapeutics. PMID:27481726

New and improved proteomics technologies for understanding complex biological systems: addressing a grand challenge in the life sciences.

PubMed

Hood, Leroy E; Omenn, Gilbert S; Moritz, Robert L; Aebersold, Ruedi; Yamamoto, Keith R; Amos, Michael; Hunter-Cevera, Jennie; Locascio, Laurie

2012-09-01

This White Paper sets out a Life Sciences Grand Challenge for Proteomics Technologies to enhance our understanding of complex biological systems, link genomes with phenotypes, and bring broad benefits to the biosciences and the US economy. The paper is based on a workshop hosted by the National Institute of Standards and Technology (NIST) in Gaithersburg, MD, 14-15 February 2011, with participants from many federal R&D agencies and research communities, under the aegis of the US National Science and Technology Council (NSTC). Opportunities are identified for a coordinated R&D effort to achieve major technology-based goals and address societal challenges in health, agriculture, nutrition, energy, environment, national security, and economic development. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In search of mitochondrial mechanisms: interfield excursions between cell biology and biochemistry.

PubMed

Bechtel, William; Abrahamsen, Adele

2007-01-01

Developing models of biological mechanisms, such as those involved in respiration in cells, often requires collaborative effort drawing upon techniques developed and information generated in different disciplines. Biochemists in the early decades of the 20th century uncovered all but the most elusive chemical operations involved in cellular respiration, but were unable to align the reaction pathways with particular structures in the cell. During the period 1940-1965 cell biology was emerging as a new discipline and made distinctive contributions to understanding the role of the mitochondrion and its component parts in cellular respiration. In particular, by developing techniques for localizing enzymes or enzyme systems in specific cellular components, cell biologists provided crucial information about the organized structures in which the biochemical reactions occurred. Although the idea that biochemical operations are intimately related to and depend on cell structures was at odds with the then-dominant emphasis on systems of soluble enzymes in biochemistry, a reconceptualization of energetic processes in the 1960s and 1970s made it clear why cell structure was critical to the biochemical account. This paper examines how numerous excursions between biochemistry and cell biology contributed a new understanding of the mechanism of cellular respiration.

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

A Tricky Trait: Applying the Fruits of the "Function Debate" in the Philosophy of Biology to the "Venom Debate" in the Science of Toxinology.

PubMed

Jackson, Timothy N W; Fry, Bryan G

2016-09-07

The "function debate" in the philosophy of biology and the "venom debate" in the science of toxinology are conceptually related. Venom systems are complex multifunctional traits that have evolved independently numerous times throughout the animal kingdom. No single concept of function, amongst those popularly defended, appears adequate to describe these systems in all their evolutionary contexts and extant variations. As such, a pluralistic view of function, previously defended by some philosophers of biology, is most appropriate. Venom systems, like many other functional traits, exist in nature as points on a continuum and the boundaries between "venomous" and "non-venomous" species may not always be clearly defined. This paper includes a brief overview of the concept of function, followed by in-depth discussion of its application to venom systems. A sound understanding of function may aid in moving the venom debate forward. Similarly, consideration of a complex functional trait such as venom may be of interest to philosophers of biology.

High definition for systems biology of microbial communities: metagenomics gets genome-centric and strain-resolved.

PubMed

Turaev, Dmitrij; Rattei, Thomas

2016-06-01

The systems biology of microbial communities, organismal communities inhabiting all ecological niches on earth, has in recent years been strongly facilitated by the rapid development of experimental, sequencing and data analysis methods. Novel experimental approaches and binning methods in metagenomics render the semi-automatic reconstructions of near-complete genomes of uncultivable bacteria possible, while advances in high-resolution amplicon analysis allow for efficient and less biased taxonomic community characterization. This will also facilitate predictive modeling approaches, hitherto limited by the low resolution of metagenomic data. In this review, we pinpoint the most promising current developments in metagenomics. They facilitate microbial systems biology towards a systemic understanding of mechanisms in microbial communities with scopes of application in many areas of our daily life. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systems biology and livestock production.

PubMed

Headon, D

2013-12-01

The mapping of complete sets of genes, transcripts and proteins from many organisms has prompted the development of new '-omic' technologies for collecting and analysing very large amounts of data. Now that the tools to generate and interrogate such complete data sets are widely used, much of the focus of biological research has begun to turn towards understanding systems as a whole, rather than studying their components in isolation. This very broadly defined systems approach is being deployed across a range of problems and scales of organisation, including many aspects of the animal sciences. Here I review selected examples of this systems approach as applied to poultry and livestock production, product quality and welfare.

Student Teachers' Pedagogical Content Knowledge for Teaching Systems Thinking: Effects of Different Interventions

ERIC Educational Resources Information Center

Rosenkränzer, Frank; Hörsch, Christian; Schuler, Stephan; Riess, Werner

2017-01-01

Systems' thinking has become increasingly relevant not only in education for sustainable development but also in everyday life. Even if teachers know the dynamics and complexity of living systems in biology and geography, they might not be able to effectively explain it to students. Teachers need an understanding of systems and their behaviour…

Strategies for structuring interdisciplinary education in Systems Biology: an European perspective

PubMed Central

Cvijovic, Marija; Höfer, Thomas; Aćimović, Jure; Alberghina, Lilia; Almaas, Eivind; Besozzi, Daniela; Blomberg, Anders; Bretschneider, Till; Cascante, Marta; Collin, Olivier; de Atauri, Pedro; Depner, Cornelia; Dickinson, Robert; Dobrzynski, Maciej; Fleck, Christian; Garcia-Ojalvo, Jordi; Gonze, Didier; Hahn, Jens; Hess, Heide Marie; Hollmann, Susanne; Krantz, Marcus; Kummer, Ursula; Lundh, Torbjörn; Martial, Gifta; dos Santos, Vítor Martins; Mauer-Oberthür, Angela; Regierer, Babette; Skene, Barbara; Stalidzans, Egils; Stelling, Jörg; Teusink, Bas; Workman, Christopher T; Hohmann, Stefan

2016-01-01

Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii) a description of possible career paths for students who undergo such an education, (iv) conditions that should improve the recruitment of students to such programmes and (v) mechanisms for collaboration and excellence spreading among education professionals. With the growing interest of industry in applying Systems Biology approaches in their fields, a concerted action between academia and industry is needed to build this expertise. Here we present a reflection of the European situation and expertise, where most of the challenges we discuss are universal, anticipating that our suggestions will be useful internationally. We believe that one of the overriding goals of any Systems Biology education should be a student’s ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively across different experimental and theoretical disciplines in research and development. PMID:28725471

Understanding the biology and control of the poultry red mite Dermanyssus gallinae: a review.

PubMed

Pritchard, James; Kuster, Tatiana; Sparagano, Olivier; Tomley, Fiona

2015-01-01

Dermanyssus gallinae, the poultry red mite (PRM), is a blood-feeding ectoparasite capable of causing pathology in birds, amongst other animals. It is an increasingly important pathogen in egg layers and is responsible for substantial economic losses to the poultry industry worldwide. Even though PRM poses a serious problem, very little is known about the basic biology of the mite. Here we review the current body of literature describing red mite biology and discuss how this has been, or could be, used to develop methods to control PRM infestations. We focus primarily on the PRM digestive system, salivary glands, nervous system and exoskeleton and also explore areas of PRM biology which have to date received little or no study but have the potential to offer new control targets.

A taxonomy of visualization tasks for the analysis of biological pathway data.

PubMed

Murray, Paul; McGee, Fintan; Forbes, Angus G

2017-02-15

Understanding complicated networks of interactions and chemical components is essential to solving contemporary problems in modern biology, especially in domains such as cancer and systems research. In these domains, biological pathway data is used to represent chains of interactions that occur within a given biological process. Visual representations can help researchers understand, interact with, and reason about these complex pathways in a number of ways. At the same time, these datasets offer unique challenges for visualization, due to their complexity and heterogeneity. Here, we present taxonomy of tasks that are regularly performed by researchers who work with biological pathway data. The generation of these tasks was done in conjunction with interviews with several domain experts in biology. These tasks require further classification than is provided by existing taxonomies. We also examine existing visualization techniques that support each task, and we discuss gaps in the existing visualization space revealed by our taxonomy. Our taxonomy is designed to support the development and design of future biological pathway visualization applications. We conclude by suggesting future research directions based on our taxonomy and motivated by the comments received by our domain experts.

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

PubMed Central

Pathak, Rajesh Kumar; Gupta, Sanjay Mohan; Gaur, Vikram Singh; Pandey, Dinesh

2015-01-01

Abstract In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes. PMID:26484978

Hydrology, phenology and the USA National Phenology Network

USGS Publications Warehouse

Kish, George R.

2010-01-01

Phenology is the study of seasonally-recurring biological events (such as leaf-out, fruit production, and animal reproduction and migration) and how these events are influenced by environmental change. Phenological changes are some of the most sensitive biological indicators of climate change, and also affect nearly all aspects of ecosystem function. Spatially extensive patterns of phenological observations have been closely linked with climate variability. Phenology and hydrology are closely linked and affect one another across a variety of scales, from leaf intercellular spaces to the troposphere, and over periods of seconds to centuries. Ecosystem life cycles and diversity are also influenced by hydrologic processes such as floods and droughts. Therefore, understanding the relationships between hydrology and phenology is increasingly important in understanding how climate change affects biological and physical systems.

Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Ueno, Kazuko; Miyano, Satoru

2009-04-27

Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC) fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe) as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules - Rule I and Rule II - to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in 1986. Our simulation results suggest that: Rule I that cannot be applied with qualitative based model checking, is more reasonable than Rule II owing to the high coverage of predicted fate patterns (except for the genotype of lin-15ko; lin-12ko double mutants). More insights are also suggested. The quantitative simulation-based model checking approach is a useful means to provide us valuable biological insights and better understandings of biological systems and observation data that may be hard to capture with the qualitative one.

Simulations in Medicine and Biology: Insights and perspectives

NASA Astrophysics Data System (ADS)

Spyrou, George M.

2015-01-01

Modern medicine and biology have been transformed into quantitative sciences of high complexity, with challenging objectives. The aims of medicine are related to early diagnosis, effective therapy, accurate intervention, real time monitoring, procedures/systems/instruments optimization, error reduction, and knowledge extraction. Concurrently, following the explosive production of biological data concerning DNA, RNA, and protein biomolecules, a plethora of questions has been raised in relation to their structure and function, the interactions between them, their relationships and dependencies, their regulation and expression, their location, and their thermodynamic characteristics. Furthermore, the interplay between medicine and biology gives rise to fields like molecular medicine and systems biology which are further interconnected with physics, mathematics, informatics, and engineering. Modelling and simulation is a powerful tool in the fields of Medicine and Biology. Simulating the phenomena hidden inside a diagnostic or therapeutic medical procedure, we are able to obtain control on the whole system and perform multilevel optimization. Furthermore, modelling and simulation gives insights in the various scales of biological representation, facilitating the understanding of the huge amounts of derived data and the related mechanisms behind them. Several examples, as well as the insights and the perspectives of simulations in biomedicine will be presented.

John Michael Yarbrough | NREL

Science.gov Websites

of his time at CSM developing and using novel characterization techniques to obtain a fundamental of imaging and spectroscopy to obtain a better fundamental understanding of biological systems and

Molecular biomimetics: utilizing nature's molecular ways in practical engineering.

PubMed

Tamerler, Candan; Sarikaya, Mehmet

2007-05-01

In nature, proteins are the machinery that accomplish many functions through their specific recognition and interactions in biological systems from single-celled to multicellular organisms. Biomolecule-material interaction is accomplished via molecular specificity, leading to the formation of controlled structures and functions at all scales of dimensional hierarchy. Through evolution, molecular recognition and, consequently, functions developed through successive cycles of mutation and selection. Using biology as a guide, we can now understand, engineer and control peptide-material interactions and exploit these to tailor novel materials and systems for practical applications. We adapted combinatorial biology protocols to display peptide libraries, either on the cell surface or on phages, to select short peptides specific to a variety of practical materials systems. Following the selection step, we determined the kinetics and stability of peptide binding experimentally to understand the bound peptide structure via modeling and its assembly via atomic force microscopy. The peptides were further engineered to have multiple repeats or their amino acid sequences varied to tailor their function. Both nanoparticles and flat inorganic substrates containing multimaterials patterned at the nano- and microscales were used for self-directed immobilization of molecular constructs. The molecular biomimetic approach opens up new avenues for the design and utilization of multifunctional molecular systems with wide ranging applications, from tissue engineering, drug delivery and biosensors, to nanotechnology and bioremediation. Here we give examples of protein-mediated functional materials in biology, peptide selection and engineering with affinity to inorganics, demonstrate potential utilizations in materials science, engineering and medicine, and describe future prospects.

Emerging biomedical applications of synthetic biology.

PubMed

Weber, Wilfried; Fussenegger, Martin

2011-11-29

Synthetic biology aims to create functional devices, systems and organisms with novel and useful functions on the basis of catalogued and standardized biological building blocks. Although they were initially constructed to elucidate the dynamics of simple processes, designed devices now contribute to the understanding of disease mechanisms, provide novel diagnostic tools, enable economic production of therapeutics and allow the design of novel strategies for the treatment of cancer, immune diseases and metabolic disorders, such as diabetes and gout, as well as a range of infectious diseases. In this Review, we cover the impact and potential of synthetic biology for biomedical applications.

Moving from the Membranes: Exploring the Integumentary System through Experiential Anatomy and Dance

ERIC Educational Resources Information Center

Kirk, Johanna

2017-01-01

This article outlines a somatic-based class that illustrates how the integumentary system can be introduced to dance students to further their understanding of their physical instruments. It justifies why incorporating information about specific biological systems into dance teaching is apt and beneficial for dancers, and it describes how guided…

Middle and High School Students' Conceptions of Climate Change Mitigation and Adaptation Strategies

ERIC Educational Resources Information Center

Bofferding, Laura; Kloser, Matthew

2015-01-01

Both scientists and policy-makers emphasize the importance of education for influencing pro-environmental behavior and minimizing the effects of climate change on biological and physical systems. Education has the potential to impact students' system knowledge--their understanding of the variables that affect the climate system--and action…

Adaptation in Living Systems

NASA Astrophysics Data System (ADS)

Tu, Yuhai; Rappel, Wouter-Jan

2018-03-01

Adaptation refers to the biological phenomenon where living systems change their internal states in response to changes in their environments in order to maintain certain key functions critical for their survival and fitness. Adaptation is one of the most ubiquitous and arguably one of the most fundamental properties of living systems. It occurs throughout all biological scales, from adaptation of populations of species over evolutionary time to adaptation of a single cell to different environmental stresses during its life span. In this article, we review some of the recent progress made in understanding molecular mechanisms of cellular-level adaptation. We take the minimalist (or the physicist) approach and study the simplest systems that exhibit generic adaptive behaviors, namely chemotaxis in bacterium cells (Escherichia coli) and eukaryotic cells (Dictyostelium). We focus on understanding the basic biochemical interaction networks that are responsible for adaptation dynamics. By combining theoretical modeling with quantitative experimentation, we demonstrate universal features in adaptation as well as important differences in different cellular systems. Future work in extending the modeling framework to study adaptation in more complex systems such as sensory neurons is also discussed.

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

Biomedical and Catalytic Opportunities of Virus-Like Particles in Nanotechnology.

PubMed

Schwarz, B; Uchida, M; Douglas, T

2017-01-01

Within biology, molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nanosystems that exist at the interface of living organisms and nonliving biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. Composed of self-assembling protein subunits, VLPs provide both a model for studying materials' assembly at the nanoscale and useful building blocks for materials design. The robustness and degree of understanding of many VLP structures allow for the ready use of these systems as versatile nanoparticle platforms for the conjugation of active molecules or as scaffolds for the structural organization of chemical processes. Lastly the prevalence of viruses in all domains of life has led to unique activities of VLPs in biological systems most notably the immune system. Here we discuss recent efforts to apply VLPs in a wide variety of applications with the aim of highlighting how the common structural elements of VLPs have led to their emergence as paradigms for the understanding and design of biological nanomaterials. © 2017 Elsevier Inc. All rights reserved.

Mathematical formalisms based on approximated kinetic representations for modeling genetic and metabolic pathways.

PubMed

Alves, Rui; Vilaprinyo, Ester; Hernádez-Bermejo, Benito; Sorribas, Albert

2008-01-01

There is a renewed interest in obtaining a systemic understanding of metabolism, gene expression and signal transduction processes, driven by the recent research focus on Systems Biology. From a biotechnological point of view, such a systemic understanding of how a biological system is designed to work can facilitate the rational manipulation of specific pathways in different cell types to achieve specific goals. Due to the intrinsic complexity of biological systems, mathematical models are a central tool for understanding and predicting the integrative behavior of those systems. Particularly, models are essential for a rational development of biotechnological applications and in understanding system's design from an evolutionary point of view. Mathematical models can be obtained using many different strategies. In each case, their utility will depend upon the properties of the mathematical representation and on the possibility of obtaining meaningful parameters from available data. In practice, there are several issues at stake when one has to decide which mathematical model is more appropriate for the study of a given problem. First, one needs a model that can represent the aspects of the system one wishes to study. Second, one must choose a mathematical representation that allows an accurate analysis of the system with respect to different aspects of interest (for example, robustness of the system, dynamical behavior, optimization of the system with respect to some production goal, parameter value determination, etc). Third, before choosing between alternative and equally appropriate mathematical representations for the system, one should compare representations with respect to easiness of automation for model set-up, simulation, and analysis of results. Fourth, one should also consider how to facilitate model transference and re-usability by other researchers and for distinct purposes. Finally, one factor that is important for all four aspects is the regularity in the mathematical structure of the equations because it facilitates computational manipulation. This regularity is a mark of kinetic representations based on approximation theory. The use of approximation theory to derive mathematical representations with regular structure for modeling purposes has a long tradition in science. In most applied fields, such as engineering and physics, those approximations are often required to obtain practical solutions to complex problems. In this paper we review some of the more popular mathematical representations that have been derived using approximation theory and are used for modeling in molecular systems biology. We will focus on formalisms that are theoretically supported by the Taylor Theorem. These include the Power-law formalism, the recently proposed (log)linear and Lin-log formalisms as well as some closely related alternatives. We will analyze the similarities and differences between these formalisms, discuss the advantages and limitations of each representation, and provide a tentative "road map" for their potential utilization for different problems.

Understanding past, contemporary, and future dynamics of plants, populations, and communities using Sonoran Desert winter annuals.

PubMed

Huxman, Travis E; Kimball, Sarah; Angert, Amy L; Gremer, Jennifer R; Barron-Gafford, Greg A; Venable, D Lawrence

2013-07-01

Global change requires plant ecologists to predict future states of biological diversity to aid the management of natural communities, thus introducing a number of significant challenges. One major challenge is considering how the many interacting features of biological systems, including ecophysiological processes, plant life histories, and species interactions, relate to performance in the face of a changing environment. We have employed a functional trait approach to understand the individual, population, and community dynamics of a model system of Sonoran Desert winter annual plants. We have used a comprehensive approach that connects physiological ecology and comparative biology to population and community dynamics, while emphasizing both ecological and evolutionary processes. This approach has led to a fairly robust understanding of past and contemporary dynamics in response to changes in climate. In this community, there is striking variation in physiological and demographic responses to both precipitation and temperature that is described by a trade-off between water-use efficiency (WUE) and relative growth rate (RGR). This community-wide trade-off predicts both the demographic and life history variation that contribute to species coexistence. Our framework has provided a mechanistic explanation to the recent warming, drying, and climate variability that has driven a surprising shift in these communities: cold-adapted species with more buffered population dynamics have increased in relative abundance. These types of comprehensive approaches that acknowledge the hierarchical nature of biology may be especially useful in aiding prediction. The emerging, novel and nonstationary climate constrains our use of simplistic statistical representations of past plant behavior in predicting the future, without understanding the mechanistic basis of change.

A Challenging Pie to Splice: Drugging the Spliceosome.

PubMed

León, Brian; Kashyap, Manoj K; Chan, Warren C; Krug, Kelsey A; Castro, Januario E; La Clair, James J; Burkart, Michael D

2017-09-25

Since its discovery in 1977, the study of alternative RNA splicing has revealed a plethora of mechanisms that had never before been documented in nature. Understanding these transitions and their outcome at the level of the cell and organism has become one of the great frontiers of modern chemical biology. Until 2007, this field remained in the hands of RNA biologists. However, the recent identification of natural product and synthetic modulators of RNA splicing has opened new access to this field, allowing for the first time a chemical-based interrogation of RNA splicing processes. Simultaneously, we have begun to understand the vital importance of splicing in disease, which offers a new platform for molecular discovery and therapy. As with many natural systems, gaining clear mechanistic detail at the molecular level is key towards understanding the operation of any biological machine. This minireview presents recent lessons learned in this emerging field of RNA splicing chemistry and chemical biology. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Understanding the complexities of Salmonella-host crosstalk as revealed by in vivo model organisms.

PubMed

Verma, Smriti; Srikanth, Chittur V

2015-07-01

Foodborne infections caused by non-typhoidal Salmonellae, such as Salmonella enterica serovar Typhimurium (ST), pose a major challenge in the developed and developing world. With constant rise of drug-resistant strains, understanding the epidemiology, microbiology, pathogenesis and host-pathogen interactions biology is a mandatory requirement to enable health systems to be ready to combat these illnesses. Patient data from hospitals, at least from some parts of the world, have aided in epidemiological understanding of ST-mediated disease. Most of the other aspects connected to Salmonella-host crosstalk have come from model systems that offer convenience, genetic tractability and low maintenance costs that make them extremely valuable tools. Complex model systems such as the bovine model have helped in understanding key virulence factors needed for infection. Simple systems such as fruit flies and Caenorhabditis elegans have aided in identification of novel virulence factors, host pathways and mechanistic details of interactions. Some of the path-breaking concepts of the field have come from mice model of ST colitis, which allows genetic manipulations as well as high degree of similarity to human counterpart. Together, they are invaluable for correlating in vitro findings of ST-induced disease progression in vivo. The current review is a compilation of various advances of ST-host interactions at cellular and molecular levels that has come from investigations involving model organisms. © 2015 International Union of Biochemistry and Molecular Biology.

Computational modeling of neural plasticity for self-organization of neural networks.

PubMed

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

ModeLang: a new approach for experts-friendly viral infections modeling.

PubMed

Wasik, Szymon; Prejzendanc, Tomasz; Blazewicz, Jacek

2013-01-01

Computational modeling is an important element of systems biology. One of its important applications is modeling complex, dynamical, and biological systems, including viral infections. This type of modeling usually requires close cooperation between biologists and mathematicians. However, such cooperation often faces communication problems because biologists do not have sufficient knowledge to understand mathematical description of the models, and mathematicians do not have sufficient knowledge to define and verify these models. In many areas of systems biology, this problem has already been solved; however, in some of these areas there are still certain problematic aspects. The goal of the presented research was to facilitate this cooperation by designing seminatural formal language for describing viral infection models that will be easy to understand for biologists and easy to use by mathematicians and computer scientists. The ModeLang language was designed in cooperation with biologists and its computer implementation was prepared. Tests proved that it can be successfully used to describe commonly used viral infection models and then to simulate and verify them. As a result, it can make cooperation between biologists and mathematicians modeling viral infections much easier, speeding up computational verification of formulated hypotheses.

ModeLang: A New Approach for Experts-Friendly Viral Infections Modeling

PubMed Central

Blazewicz, Jacek

2013-01-01

Computational modeling is an important element of systems biology. One of its important applications is modeling complex, dynamical, and biological systems, including viral infections. This type of modeling usually requires close cooperation between biologists and mathematicians. However, such cooperation often faces communication problems because biologists do not have sufficient knowledge to understand mathematical description of the models, and mathematicians do not have sufficient knowledge to define and verify these models. In many areas of systems biology, this problem has already been solved; however, in some of these areas there are still certain problematic aspects. The goal of the presented research was to facilitate this cooperation by designing seminatural formal language for describing viral infection models that will be easy to understand for biologists and easy to use by mathematicians and computer scientists. The ModeLang language was designed in cooperation with biologists and its computer implementation was prepared. Tests proved that it can be successfully used to describe commonly used viral infection models and then to simulate and verify them. As a result, it can make cooperation between biologists and mathematicians modeling viral infections much easier, speeding up computational verification of formulated hypotheses. PMID:24454531

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Sealable femtoliter chamber arrays for cell-free biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Retterer, Scott T.; Fowlkes, Jason Davidson; Collier, Charles Patrick

Cell-free systems provide a flexible platform for probing specific networks of biological reactions isolated from the complex resource sharing (e.g. global gene expression, cell division) encountered within living cells. However, such systems, used in conventional macro-scale bulk reactors, often fail to exhibit the dynamic behaviors and efficiencies characteristic of their living micro-scale counterparts. Understanding the impact of internal cell structure and scale on reaction dynamics is crucial to understanding complex gene networks. Here we report a microfabricated device that confines cell-free reactions in cellular scale volumes while allowing flexible characterization of the enclosed molecular system. This multilayered poly(dimethylsiloxane) (PDMS) devicemore » contains femtoliter-scale reaction chambers on an elastomeric membrane which can be actuated (open and closed). When actuated, the chambers confine Cell-Free Protein Synthesis (CFPS) reactions expressing a fluorescent protein, allowing for the visualization of the reaction kinetics over time using time-lapse fluorescent microscopy. Lastly, we demonstrate how this device may be used to measure the noise structure of CFPS reactions in a manner that is directly analogous to those used to characterize cellular systems, thereby enabling the use of noise biology techniques to characterize CFPS gene circuits and their interactions with the cell-free environment.« less

Sealable femtoliter chamber arrays for cell-free biology

DOE PAGES

Retterer, Scott T.; Fowlkes, Jason Davidson; Collier, Charles Patrick; ...

2015-03-11

Cell-free systems provide a flexible platform for probing specific networks of biological reactions isolated from the complex resource sharing (e.g. global gene expression, cell division) encountered within living cells. However, such systems, used in conventional macro-scale bulk reactors, often fail to exhibit the dynamic behaviors and efficiencies characteristic of their living micro-scale counterparts. Understanding the impact of internal cell structure and scale on reaction dynamics is crucial to understanding complex gene networks. Here we report a microfabricated device that confines cell-free reactions in cellular scale volumes while allowing flexible characterization of the enclosed molecular system. This multilayered poly(dimethylsiloxane) (PDMS) devicemore » contains femtoliter-scale reaction chambers on an elastomeric membrane which can be actuated (open and closed). When actuated, the chambers confine Cell-Free Protein Synthesis (CFPS) reactions expressing a fluorescent protein, allowing for the visualization of the reaction kinetics over time using time-lapse fluorescent microscopy. Lastly, we demonstrate how this device may be used to measure the noise structure of CFPS reactions in a manner that is directly analogous to those used to characterize cellular systems, thereby enabling the use of noise biology techniques to characterize CFPS gene circuits and their interactions with the cell-free environment.« less

Biomaterial science meets computational biology.

PubMed

Hutmacher, Dietmar W; Little, J Paige; Pettet, Graeme J; Loessner, Daniela

2015-05-01

There is a pressing need for a predictive tool capable of revealing a holistic understanding of fundamental elements in the normal and pathological cell physiology of organoids in order to decipher the mechanoresponse of cells. Therefore, the integration of a systems bioengineering approach into a validated mathematical model is necessary to develop a new simulation tool. This tool can only be innovative by combining biomaterials science with computational biology. Systems-level and multi-scale experimental data are incorporated into a single framework, thus representing both single cells and collective cell behaviour. Such a computational platform needs to be validated in order to discover key mechano-biological factors associated with cell-cell and cell-niche interactions.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology.

PubMed

Rubenstein, Michael; Sai, Ying; Chuong, Cheng-Ming; Shen, Wei-Min

2009-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology

PubMed Central

RUBENSTEIN, MICHAEL; SAI, YING; CHUONG, CHENG-MING; SHEN, WEI-MIN

2010-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. “Self” here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering. PMID:19557691

Computational dynamic approaches for temporal omics data with applications to systems medicine.

PubMed

Liang, Yulan; Kelemen, Arpad

2017-01-01

Modeling and predicting biological dynamic systems and simultaneously estimating the kinetic structural and functional parameters are extremely important in systems and computational biology. This is key for understanding the complexity of the human health, drug response, disease susceptibility and pathogenesis for systems medicine. Temporal omics data used to measure the dynamic biological systems are essentials to discover complex biological interactions and clinical mechanism and causations. However, the delineation of the possible associations and causalities of genes, proteins, metabolites, cells and other biological entities from high throughput time course omics data is challenging for which conventional experimental techniques are not suited in the big omics era. In this paper, we present various recently developed dynamic trajectory and causal network approaches for temporal omics data, which are extremely useful for those researchers who want to start working in this challenging research area. Moreover, applications to various biological systems, health conditions and disease status, and examples that summarize the state-of-the art performances depending on different specific mining tasks are presented. We critically discuss the merits, drawbacks and limitations of the approaches, and the associated main challenges for the years ahead. The most recent computing tools and software to analyze specific problem type, associated platform resources, and other potentials for the dynamic trajectory and interaction methods are also presented and discussed in detail.

6th Institute for Systems Biology International Symposium: Systems Biology and the Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Galitski, Timothy P.

2007-04-23

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology is an annual two-day event gathering the most influential researchers transforming biology into an integrative discipline investigating complex systems. In recognition of the fundamental similarity between the scientific problems addressed in environmental science and systems biology studies at the molecular, cellular, and organismal levels, the 2007 Symposium featured global leaders in “Systems Biology and the Environment.” The objective of the 2007 “Systems Biology and the Environment” International Symposium was to stimulate interdisciplinary thinking and research that spans systems biology andmore » environmental science. This Symposium was well aligned with the DOE’s Genomics: GTL program efforts to achieve scientific objectives for each of the three DOE missions: Develop biofuels as a major secure energy source for this century; Develop biological solutions for intractable environmental problems; Understand biosystems’ climate impacts and assess sequestration strategies. Our scientific program highlighted world-class research exemplifying these priorities. The Symposium featured 45 minute lectures from 12 researchers including: Penny/Sallie Chisholm of MIT gave the keynote address “Tiny Cells, Global Impact: What Prochlorococcus Can Teach Us About Systems Biology”, plus Jim Fredrickson of PNNL, Nitin Baliga of ISB, Steve Briggs of UCSD, David Cox of Perlegen Sciences, Antoine Danchin of Institut Pasteur, John Delaney of the U of Washington, John Groopman of Johns Hopkins, Ben Kerr of the U of Washington, Steve Koonin of BP, Elliott Meyerowitz of Caltech, and Ed Rubin of LBNL. The 2007 Symposium promoted DOE’s three mission areas among scientists from multiple disciplines representing academia, non-profit research institutions, and the private sector. As in all previous Symposia, we had excellent attendance of participants representing 20-30 academic or research-oriented facilities along with 25-30 private corporations from 5-10 countries. To broaden the audience for the Symposium and ensure the continued accessibility of the presentations, we made the presentation videos available afterward on the ISB’s website.« less

An overview of bioinformatics methods for modeling biological pathways in yeast.

PubMed

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

2016-03-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Systems Biology Approaches for Understanding Genome Architecture.

PubMed

Sewitz, Sven; Lipkow, Karen

2016-01-01

The linear and three-dimensional arrangement and composition of chromatin in eukaryotic genomes underlies the mechanisms directing gene regulation. Understanding this organization requires the integration of many data types and experimental results. Here we describe the approach of integrating genome-wide protein-DNA binding data to determine chromatin states. To investigate spatial aspects of genome organization, we present a detailed description of how to run stochastic simulations of protein movements within a simulated nucleus in 3D. This systems level approach enables the development of novel questions aimed at understanding the basic mechanisms that regulate genome dynamics.

Toward High School Biology: Helping Middle School Students Understand Chemical Reactions and Conservation of Mass in Nonliving and Living Systems

PubMed Central

Herrmann-Abell, Cari F.; Koppal, Mary; Roseman, Jo Ellen

2016-01-01

Modern biology has become increasingly molecular in nature, requiring students to understand basic chemical concepts. Studies show, however, that many students fail to grasp ideas about atom rearrangement and conservation during chemical reactions or the application of these ideas to biological systems. To help provide students with a better foundation, we used research-based design principles and collaborated in the development of a curricular intervention that applies chemistry ideas to living and nonliving contexts. Six eighth grade teachers and their students participated in a test of the unit during the Spring of 2013. Two of the teachers had used an earlier version of the unit the previous spring. The other four teachers were randomly assigned either to implement the unit or to continue teaching the same content using existing materials. Pre- and posttests were administered, and the data were analyzed using Rasch modeling and hierarchical linear modeling. The results showed that, when controlling for pretest score, gender, language, and ethnicity, students who used the curricular intervention performed better on the posttest than the students using existing materials. Additionally, students who participated in the intervention held fewer misconceptions. These results demonstrate the unit’s promise in improving students’ understanding of the targeted ideas. PMID:27909024

Understanding Randomness and its Impact on Student Learning: Lessons Learned from Building the Biology Concept Inventory (BCI)

PubMed Central

Garvin-Doxas, Kathy

2008-01-01

While researching student assumptions for the development of the Biology Concept Inventory (BCI; http://bioliteracy.net), we found that a wide class of student difficulties in molecular and evolutionary biology appears to be based on deep-seated, and often unaddressed, misconceptions about random processes. Data were based on more than 500 open-ended (primarily) college student responses, submitted online and analyzed through our Ed's Tools system, together with 28 thematic and think-aloud interviews with students, and the responses of students in introductory and advanced courses to questions on the BCI. Students believe that random processes are inefficient, whereas biological systems are very efficient. They are therefore quick to propose their own rational explanations for various processes, from diffusion to evolution. These rational explanations almost always make recourse to a driver, e.g., natural selection in evolution or concentration gradients in molecular biology, with the process taking place only when the driver is present, and ceasing when the driver is absent. For example, most students believe that diffusion only takes place when there is a concentration gradient, and that the mutational processes that change organisms occur only in response to natural selection pressures. An understanding that random processes take place all the time and can give rise to complex and often counterintuitive behaviors is almost totally absent. Even students who have had advanced or college physics, and can discuss diffusion correctly in that context, cannot make the transfer to biological processes, and passing through multiple conventional biology courses appears to have little effect on their underlying beliefs. PMID:18519614

Understand the cogs to understand cognition.

PubMed

Marblestone, Adam H; Wayne, Greg; Kording, Konrad P

2017-01-01

Lake et al. suggest that current AI systems lack the inductive biases that enable human learning. However, Lake et al.'s proposed biases may not directly map onto mechanisms in the developing brain. A convergence of fields may soon create a correspondence between biological neural circuits and optimization in structured architectures, allowing us to systematically dissect how brains learn.

Prospective Elementary Science Teachers' Understanding of Photosynthesis and Cellular Respiration in the Context of Multiple Biological Levels as Nested Systems

ERIC Educational Resources Information Center

Akçay, Süleyman

2017-01-01

In this study, Turkish prospective elementary science teachers' understanding of photosynthesis and cellular respiration has been analysed within the contexts of ecosystem knowledge, organism knowledge and interconnection knowledge (IK). In the analysis, concept maps developed by 74 prospective teachers were used. The study was carried out with…

Perceived Discrimination, Racial Identity, and Multisystem Stress Response to Social Evaluative Threat Among African American Men and Women.

PubMed

Lucas, Todd; Wegner, Rhiana; Pierce, Jennifer; Lumley, Mark A; Laurent, Heidemarie K; Granger, Douglas A

2017-04-01

Understanding individual differences in the psychobiology of the stress response is critical to grasping how psychosocial factors contribute to racial and ethnic health disparities. However, the ways in which environmentally sensitive biological systems coordinate in response to acute stress is not well understood. We used a social-evaluative stress task to investigate coordination among the autonomic nervous system, hypothalamic-pituitary-adrenal axis, and immune/inflammatory system in a community sample of 85 healthy African American men and women. Six saliva samples, 2 at each of baseline, event, and recovery phases of the stressor task, were assayed for cortisol, dehydroepiandrosterone-sulfate, salivary alpha-amylase, and salivary C-reactive protein. Individual differences in perceived discrimination and racial identity were also measured. Factor analysis demonstrated that stress systems were largely dissociated before stressor exposure but became aligned during event and recovery phases into functional biological stress responses (factor loadings ≥ .58). Coordinated responses were related to interactions of perceived discrimination and racial identity: when racial identity was strong, highly perceived discrimination was associated with low hypothalamic-pituitary-adrenal axis activity at baseline (B's = .68-.72, p < .001), low stress mobilization during the task (B's = .46-.62, p < .049), and a robust inflammatory response (salivary C-reactive protein) during recovery (B's = .72-.94, p < .002). Culturally relevant social perceptions may be linked to a specific pattern of changing alignment in biological components of the stress response. Better understanding these links may significantly advance understanding of stress-related illnesses and disparities.

Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

NASA Astrophysics Data System (ADS)

Christensen, Claire Petra

Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author's own publications have contributed network inference, simulation, modeling, and analysis methods to the much larger body of work in systems biology, and indeed, in network science. The aim of this thesis is therefore twofold: to present this original work in the historical context of network science, but also to provide sufficient review and reference regarding complex systems (with an emphasis on complex networks in systems biology) and tools and techniques for their inference, simulation, analysis, and modeling, such that the reader will be comfortable in seeking out further information on the subject. The review-like Chapters 1, 2, and 4 are intended to convey the co-evolution of network science and the slow but noticeable breakdown of boundaries between disciplines in academia as research and comparison of diverse systems has brought to light the shared properties of these systems. It is the author's hope that theses chapters impart some sense of the remarkable and rapid progress in complex systems research that has led to this unprecedented academic synergy. Chapters 3 and 5 detail the author's original work in the context of complex systems research. Chapter 3 presents the methods and results of a two-stage modeling process that generates candidate gene-regulatory networks of the bacterium B.subtilis from experimentally obtained, yet mathematically underdetermined microchip array data. These networks are then analyzed from a graph theoretical perspective, and their biological viability is critiqued by comparing the networks' graph theoretical properties to those of other biological systems. The results of topological perturbation analyses revealing commonalities in behavior at multiple levels of complexity are also presented, and are shown to be an invaluable means by which to ascertain the level of complexity to which the network inference process is robust to noise. Chapter 5 outlines a learning algorithm for the development of a realistic, evolving social network (a city) into which a disease is introduced. The results of simulations in populations spanning two orders of magnitude are compared to prevaccine era measles data for England and Wales and demonstrate that the simulations are able to capture the quantitative and qualitative features of epidemics in populations as small as 10,000 people. The work presented in Chapter 5 validates the utility of network simulation in concurrently probing contact network dynamics and disease dynamics.

Rethinking biology instruction: The application of DNR-based instruction to the learning and teaching of biology

NASA Astrophysics Data System (ADS)

Maskiewicz, April Lee

Educational studies report that secondary and college level students have developed only limited understandings of the most basic biological processes and their interrelationships from typical classroom experiences. Furthermore, students have developed undesirable reasoning schemes and beliefs that directly affect how they make sense of and account for biological phenomena. For these reasons, there exists a need to rethink instructional practices in biology. This dissertation discusses how the principles of Harel's (1998, 2001) DNR-based instruction in mathematics could be applied to the teaching and learning of biology. DNR is an acronym for the three foundational principles of the system: Duality, Necessity, and Repeated-reasoning. This study examines the application of these three principles to ecology instruction. Through clinical and teaching interviews, I developed models of students' existing ways of understanding in ecology and inferred their ways of thinking. From these models a hypothetical learning trajectory was developed for 16 college level freshmen enrolled in a 10-week ecology teaching experiment. Through cyclical, interpretive analysis I documented and analyzed the evolution of the participants' progress. The results provide empirical evidence to support the claim that the DNR principles are applicable to ecology instruction. With respect to the Duality Principle, helping students develop specific ways of understanding led to the development of model-based reasoning---a way of thinking and the cognitive objective guiding instruction. Through carefully structured problem solving tasks, the students developed a biological understanding of the relationship between matter cycling, energy flow, and cellular processes such as photosynthesis and respiration, and used this understanding to account for observable phenomena in nature. In the case of intellectual necessity, the results illuminate how problem situations can be developed for biology learners that create cognitive disequilibrium-equilibrium phases and thus lead to modification or refinement of existing schemes. Elements that contributed to creating intellectual need include (a) problem tasks that built on students' existing knowledge; (b) problem tasks that challenged students; (c) a routine in which students presented their group's solution to the class; and (d) the didactical contract (Brousseau, 1997) established in the classroom.

The Future of Weapons of Mass Destruction: Their Nature and Role in 2030

DTIC Science & Technology

2014-06-01

substantial improvements are al- lowed under the rubric of life extension. Other states are not so constrained and may find different ways to develop pure...The foregoing capabilities do not involve genetic manipulation or bioen- gineering; they utilize longstanding biological knowledge and processes. More...sophisticated understanding of biological systems (genomic and proteomic infor- mation) and processes ( genetic modification, bioengineering) for

Soil biology research across latitude, elevation and disturbance gradients: A review of forest studies from Puerto Rico during the past 25 years

Treesearch

Grizelle González; D. Lodge

2017-01-01

Progress in understanding changes in soil biology in response to latitude, elevation and disturbance gradients has generally lagged behind studies of above-ground plants and animals owing to methodological constraints and high diversity and complexity of interactions in below-ground food webs. New methods have opened research opportunities in below-ground systems,...

Toward High School Biology: Helping Middle School Students Understand Chemical Reactions and Conservation of Mass in Nonliving and Living Systems.

PubMed

Herrmann-Abell, Cari F; Koppal, Mary; Roseman, Jo Ellen

2016-01-01

Modern biology has become increasingly molecular in nature, requiring students to understand basic chemical concepts. Studies show, however, that many students fail to grasp ideas about atom rearrangement and conservation during chemical reactions or the application of these ideas to biological systems. To help provide students with a better foundation, we used research-based design principles and collaborated in the development of a curricular intervention that applies chemistry ideas to living and nonliving contexts. Six eighth grade teachers and their students participated in a test of the unit during the Spring of 2013. Two of the teachers had used an earlier version of the unit the previous spring. The other four teachers were randomly assigned either to implement the unit or to continue teaching the same content using existing materials. Pre- and posttests were administered, and the data were analyzed using Rasch modeling and hierarchical linear modeling. The results showed that, when controlling for pretest score, gender, language, and ethnicity, students who used the curricular intervention performed better on the posttest than the students using existing materials. Additionally, students who participated in the intervention held fewer misconceptions. These results demonstrate the unit's promise in improving students' understanding of the targeted ideas. © 2016 C. F. Herrmann-Abell et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Using remote sensing to monitor past changes and assess future scenarios for the Sacramento-San Joaquin River Delta waterways, California USA

NASA Astrophysics Data System (ADS)

Santos, Maria J.; Hestir, Erin; Khanna, Shruti; Ustin, Susan L.

2017-04-01

Historically, deltas have been extensively affected both by natural processes and human intervention. Thus, understanding drivers, predicting impacts and optimizing solutions to delta problems requires a holistic approach spanning many sectors, disciplines and fields of expertise. Deltas are ideal model systems to understand the effects of the interaction between social and ecological domains, as they face unprecedented disturbances and threats to their biological and ecological sustainability. The challenge for deltas is to meet the goals of supporting biodiversity and ecosystem processes while also provisioning fresh water resources for human use. We provide an overview of the last 150 years of the Sacramento-San Joaquin River delta, where we illustrate the parallel process of an increase in disturbances, by particularly zooming in on the current cascading effects of invasive species on geophysical and biological processes. Using remote sensing data coupled with in situ measurements of water quality, turbidity, and species presence we show how the spread and persistence of aquatic invasive species affects sedimentation processes and ecosystem functioning. Our results show that the interactions between the biological and physical conditions in the Delta affect the trajectory of dominance by native and invasive aquatic plant species. Trends in growth and community characteristics associated with predicted impacts of climate change (sea level rise, warmer temperatures, changes in the hydrograph with high winter and low summer outflows) do not provide simple predictions. Individually, the impact of specific environmental changes on the biological components can be predicted, however it is the complex interactions of biological communities with the suite of physical changes that make predictions uncertain. Systematic monitoring is critical to provide the data needed to document and understand change of these delta systems, and to identify successful adaptation strategies.

[New materia medica project: synthetic biology based bioactive metabolites research in medicinal plant].

PubMed

Wang, Yong

2017-03-25

In the last decade, synthetic biology research has been gradually transited from monocellular parts or devices toward more complex multicellular systems. The emerging plant synthetic biology is regarded as the "next chapter" of synthetic biology. The complex and diverse plant metabolism as the entry point, plant synthetic biology research not only helps us understand how real life is working, but also facilitates us to learn how to design and construct more complex artificial life. Bioactive compounds innovation and large-scale production are expected to be breakthrough with the redesigned plant metabolism as well. In this review, we discuss the research progress in plant synthetic biology and propose the new materia medica project to lift the level of traditional Chinese herbal medicine research.

Bioinformatics for transporter pharmacogenomics and systems biology: data integration and modeling with UML.

PubMed

Yan, Qing

2010-01-01

Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.

Perceived Discrimination, Racial Identity, and Multisystem Stress Response to Social Evaluative Threat Among African American Men and Women

PubMed Central

Lucas, Todd; Wegner, Rhiana; Pierce, Jennifer; Lumley, Mark A.; Laurent, Heidemarie K.; Granger, Douglas A.

2015-01-01

Objective Understanding individual differences in the psychobiology of the stress response is critical to grasping how psychosocial factors contribute to racial and ethnic health disparities. However, the ways in which environmentally sensitive biological systems coordinate in response to acute stress is not well understood. We employed a social-evaluative stressor task to investigate coordination among the autonomic nervous system (ANS), hypothalamic-pituitary-adrenal (HPA) axis, immune/inflammatory system, and neurotrophic response system in a community sample of 85 healthy African American men and women. Methods Six saliva samples – two collected before and four collected during and after the stressor – were assayed for cortisol and dehydroepiandrosterone-sulfate (DHEAs; HPA-axis markers), salivary α amylase (sAA; ANS marker), salivary c-reactive protein (sCRP; inflammatory/immune marker), and salivary nerve growth factor (sNGF; neurotrophic marker). Individual differences in perceived discrimination and racial identity were also measured. Results Factor analysis demonstrated that stress systems were largely dissociated before stressor exposure, but became aligned during event and recovery phases into functional biological stress responses (factor loadings .71to.96). Coordinated responses were related to interactions of perceived discrimination and racial identity: when racial identity was strong, high perceived discrimination was associated with low hypothalamic-pituitary-adrenal (HPA) axis arousal at baseline (B’s = .68 to.72, p < .001) and during the task (B’s =.46 to .62, p ≤ .049), and a robust inflammatory response (sCRP) during recovery (B’s =.72 to.94, p ≤ .002). Conclusion Culturally-relevant social perceptions are linked to a specific pattern of changing alignment in biological stress responses. Better understanding these links may significantly advance understanding of stress-related illnesses and health disparities. PMID:27806018

A pharma perspective on the systems medicine and pharmacology of inflammation.

PubMed

Lahoz-Beneytez, Julio; Schnizler, Katrin; Eissing, Thomas

2015-02-01

Biological systems are complex and comprehend multiple scales of organisation. Hence, holistic approaches are necessary to capture the behaviour of these entities from the molecular and cellular to the whole organism level. This also applies to the understanding and treatment of different diseases. Traditional systems biology has been successful in describing different biological phenomena at the cellular level, but it still lacks of a holistic description of the multi-scale interactions within the body. The importance of the physiological context is of particular interest in inflammation. Regulatory agencies have urged the scientific community to increase the translational power of bio-medical research and it has been recognised that modelling and simulation could be a path to follow. Interestingly, in pharma R&D, modelling and simulation has been employed since a long time ago. Systems pharmacology, and particularly physiologically based pharmacokinetic/pharmacodynamic models, serve as a suitable framework to integrate the available and emerging knowledge at different levels of the drug development process. Systems medicine and pharmacology of inflammation will potentially benefit from this framework in order to better understand inflammatory diseases and to help to transfer the vast knowledge on the molecular and cellular level into a more physiological context. Ultimately, this may lead to reliable predictions of clinical outcomes such as disease progression or treatment efficacy, contributing thereby to a better care of patients. Copyright © 2014 Elsevier Inc. All rights reserved.

Mass fractionation processes of transition metal isotopes

NASA Astrophysics Data System (ADS)

Zhu, X. K.; Guo, Y.; Williams, R. J. P.; O'Nions, R. K.; Matthews, A.; Belshaw, N. S.; Canters, G. W.; de Waal, E. C.; Weser, U.; Burgess, B. K.; Salvato, B.

2002-06-01

Recent advances in mass spectrometry make it possible to utilise isotope variations of transition metals to address some important issues in solar system and biological sciences. Realisation of the potential offered by these new isotope systems however requires an adequate understanding of the factors controlling their isotope fractionation. Here we show the results of a broadly based study on copper and iron isotope fractionation during various inorganic and biological processes. These results demonstrate that: (1) naturally occurring inorganic processes can fractionate Fe isotope to a detectable level even at temperature ˜1000°C, which challenges the previous view that Fe isotope variations in natural system are unique biosignatures; (2) multiple-step equilibrium processes at low temperatures may cause large mass fractionation of transition metal isotopes even when the fractionation per single step is small; (3) oxidation-reduction is an importation controlling factor of isotope fractionation of transition metal elements with multiple valences, which opens a wide range of applications of these new isotope systems, ranging from metal-silicate fractionation in the solar system to uptake pathways of these elements in biological systems; (4) organisms incorporate lighter isotopes of transition metals preferentially, and transition metal isotope fractionation occurs stepwise along their pathways within biological systems during their uptake.

Metal stable isotopes in low-temperature systems: A primer

USGS Publications Warehouse

Bullen, T.D.; Eisenhauer, A.

2009-01-01

Recent advances in mass spectrometry have allowed isotope scientists to precisely determine stable isotope variations in the metallic elements. Biologically infl uenced and truly inorganic isotope fractionation processes have been demonstrated over the mass range of metals. This Elements issue provides an overview of the application of metal stable isotopes to low-temperature systems, which extend across the borders of several science disciplines: geology, hydrology, biology, environmental science, and biomedicine. Information on instrumentation, fractionation processes, data-reporting terminology, and reference materials presented here will help the reader to better understand this rapidly evolving field.

Pattern formation and collective effects in populations of magnetic microswimmers

NASA Astrophysics Data System (ADS)

Vach, Peter J.; Walker, Debora; Fischer, Peer; Fratzl, Peter; Faivre, Damien

2017-03-01

Self-propelled particles are one prototype of synthetic active matter used to understand complex biological processes, such as the coordination of movement in bacterial colonies or schools of fishes. Collective patterns such as clusters were observed for such systems, reproducing features of biological organization. However, one limitation of this model is that the synthetic assemblies are made of identical individuals. Here we introduce an active system based on magnetic particles at colloidal scales. We use identical but also randomly-shaped magnetic micropropellers and show that they exhibit dynamic and reversible pattern formation.

Toward a multiscale modeling framework for understanding serotonergic function

PubMed Central

Wong-Lin, KongFatt; Wang, Da-Hui; Moustafa, Ahmed A; Cohen, Jeremiah Y; Nakamura, Kae

2017-01-01

Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin. PMID:28417684

Progress in bioinformatics and the importance of being earnest.

PubMed

Attwood, T K; Miller, C J

2002-01-01

In silico biology has gathered momentum as, worldwide, scientists have united in a common quest to sequence, store and analyse complete genomes. This year, a pivotal achievement of this cooperative endeavour was realised in the release of a public draft of the human genome, and with it the promises to improve our understanding of diverse aspects of biology and to yield a healthier future with safe personalized medicines. Key to these goals will be the need to elucidate and characterise the genes and gene products encoded not just in the human genome, but in many genomes. These tasks are underpinned by the concepts and processes of genome and gene/protein evolution, regulation of gene expression, mechanisms of protein folding, the manifestation of protein function, and so on, all of which must be understood in the context of complex, dynamic biological systems. Our use of computers to model such concepts and systems must be placed in the context of the current limits of our understanding of them:- it is important to recognise, for example, that we don't have a common understanding either of what constitutes a gene or a protein function; we can't invariably say that a particular sequence or fold has arisen via divergent or convergent evolution; and we don't fully understand the rules of protein folding. Accepting what we can't do in silico is essential in appreciating what we can do. Without this understanding, it is easy to be misled, as notions of what particular computational approaches can achieve are sometimes rather optimistic. There are valuable lessons to be learned here from the field of Artificial Intelligence, principal among which is the realisation that capturing and representing complex knowledge is time consuming, expensive and hard. Thus, we argue here that if bioinformatics is to tackle biological complexity in earnest, it would be wise to absorb the experience distilled from decades of artificial intelligence research, and to approach the road ahead with caution, rigour and pragmatism.

Systems microscopy: an emerging strategy for the life sciences.

PubMed

Lock, John G; Strömblad, Staffan

2010-05-01

Dynamic cellular processes occurring in time and space are fundamental to all physiology and disease. To understand complex and dynamic cellular processes therefore demands the capacity to record and integrate quantitative multiparametric data from the four spatiotemporal dimensions within which living cells self-organize, and to subsequently use these data for the mathematical modeling of cellular systems. To this end, a raft of complementary developments in automated fluorescence microscopy, cell microarray platforms, quantitative image analysis and data mining, combined with multivariate statistics and computational modeling, now coalesce to produce a new research strategy, "systems microscopy", which facilitates systems biology analyses of living cells. Systems microscopy provides the crucial capacities to simultaneously extract and interrogate multiparametric quantitative data at resolution levels ranging from the molecular to the cellular, thereby elucidating a more comprehensive and richly integrated understanding of complex and dynamic cellular systems. The unique capacities of systems microscopy suggest that it will become a vital cornerstone of systems biology, and here we describe the current status and future prospects of this emerging field, as well as outlining some of the key challenges that remain to be overcome. Copyright 2010 Elsevier Inc. All rights reserved.

Monitoring of human populations for early markers of cadmium toxicity: A review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, Bruce A.

2009-08-01

Exposure of human populations to cadmium (Cd) from air, food and water may produce effects in organs such as the kidneys, liver, lungs, cardiovascular, immune and reproductive systems. Since Cd has been identified as a human carcinogen, biomarkers for early detection of susceptibility to cancer are of an importance to public health. The ability to document Cd exposure and uptake of this element through biological monitoring is a first step towards understanding its health effects. Interpretation and application of biological monitoring data for predicting human health outcomes require correlation with biological measures of organ system responses to the documented exposure.more » Essential to this understanding is the detection and linkage of early biological responses toxic effects in target cell populations. Fortunately, advances in cell biology have resulted in the development of pre-clinical biological markers (biomarkers) that demonstrate measurable and characteristic molecular changes in organ systems following chemical exposures that occur prior to the onset of overt clinical disease or development of cancer. Technical advances have rendered a number of these biomarkers practical for monitoring Cd-exposed human populations. Biomarkers will be increasingly important in relation to monitoring effects from the exposure to new Cd-based high technology materials. For example, cadmium-selenium (CdSe), nano-materials made from combinations of these elements have greatly altered cellular uptake characteristics due to particle size. These differences may greatly alter effects at the target cell level and hence risks for organ toxicities from such exposures. The value of validated biomarkers for early detection of systemic Cd-induced effects in humans cannot be underestimated due to the rapid expansion of nano-material technologies. This review will attempt to briefly summarize the applications, to date, of biomarker endpoints for assessing target organ system effects in humans and experimental systems from Cd exposure. Further, it will attempt to provide a prospective look at the possible future of biomarkers. The emphasis will be on the detection of early toxic effects from exposure to Cd in new products such as nano-materials and identification of populations at special risk for Cd toxicity.« less

Monitoring of human populations for early markers of cadmium toxicity: a review.

PubMed

Fowler, Bruce A

2009-08-01

Exposure of human populations to cadmium (Cd) from air, food and water may produce effects in organs such as the kidneys, liver, lungs, cardiovascular, immune and reproductive systems. Since Cd has been identified as a human carcinogen, biomarkers for early detection of susceptibility to cancer are of an importance to public health. The ability to document Cd exposure and uptake of this element through biological monitoring is a first step towards understanding its health effects. Interpretation and application of biological monitoring data for predicting human health outcomes require correlation with biological measures of organ system responses to the documented exposure. Essential to this understanding is the detection and linkage of early biological responses toxic effects in target cell populations. Fortunately, advances in cell biology have resulted in the development of pre-clinical biological markers (biomarkers) that demonstrate measurable and characteristic molecular changes in organ systems following chemical exposures that occur prior to the onset of overt clinical disease or development of cancer. Technical advances have rendered a number of these biomarkers practical for monitoring Cd-exposed human populations. Biomarkers will be increasingly important in relation to monitoring effects from the exposure to new Cd-based high technology materials. For example, cadmium-selenium (CdSe), nano-materials made from combinations of these elements have greatly altered cellular uptake characteristics due to particle size. These differences may greatly alter effects at the target cell level and hence risks for organ toxicities from such exposures. The value of validated biomarkers for early detection of systemic Cd-induced effects in humans cannot be underestimated due to the rapid expansion of nano-material technologies. This review will attempt to briefly summarize the applications, to date, of biomarker endpoints for assessing target organ system effects in humans and experimental systems from Cd exposure. Further, it will attempt to provide a prospective look at the possible future of biomarkers. The emphasis will be on the detection of early toxic effects from exposure to Cd in new products such as nano-materials and identification of populations at special risk for Cd toxicity.

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Health Belief Systems and the Psychobiology of War

PubMed Central

Elgee, Neil J.

1984-01-01

Belief systems overlie powerful biological and psychological forces that are root causes of war. Much as in medicine where an appreciation of health belief systems is necessary in the control of illness and disease, so the paths to the control of war may lie in an understanding of belief systems and ways to circumvent them. Such understanding gives strong theoretical support to many time-honored but underutilized international initiative and educational ventures. The effort of the medical community to educate the public about biomedical aspects of nuclear war should gain more balance and sophistication with an appreciation of belief systems in the psychobiology of war. PMID:6741137

APPLYING DATA MINING APPROACHES TO FURTHER UNDERSTANDING CHEMICAL EFFECTS ON BIOLOGICAL SYSTEMS.

EPA Science Inventory

Correlations of bioassays and toxicity cannot be assessed at the compound level with the current toxicity database. Further work is planned for gaining molecular level knoweldge from these experiments.

Understanding Kidney Disease: Toward the Integration of Regulatory Networks Across Species

PubMed Central

Ju, Wenjun; Brosius, Frank C.

2010-01-01

Animal models have long been useful in investigating both normal and abnormal human physiology. Systems biology provides a relatively new set of approaches to identify similarities and differences between animal models and humans that may lead to a more comprehensive understanding of human kidney pathophysiology. In this review, we briefly describe how genome-wide analyses of mouse models have helped elucidate features of human kidney diseases, discuss strategies to achieve effective network integration, and summarize currently available web-based tools that may facilitate integration of data across species. The rapid progress in systems biology and orthology, as well as the advent of web-based tools to facilitate these processes, now make it possible to take advantage of knowledge from distant animal species in targeted identification of regulatory networks that may have clinical relevance for human kidney diseases. PMID:21044762

Mainstreaming Caenorhabditis elegans in experimental evolution.

PubMed

Gray, Jeremy C; Cutter, Asher D

2014-03-07

Experimental evolution provides a powerful manipulative tool for probing evolutionary process and mechanism. As this approach to hypothesis testing has taken purchase in biology, so too has the number of experimental systems that use it, each with its own unique strengths and weaknesses. The depth of biological knowledge about Caenorhabditis nematodes, combined with their laboratory tractability, positions them well for exploiting experimental evolution in animal systems to understand deep questions in evolution and ecology, as well as in molecular genetics and systems biology. To date, Caenorhabditis elegans and related species have proved themselves in experimental evolution studies of the process of mutation, host-pathogen coevolution, mating system evolution and life-history theory. Yet these organisms are not broadly recognized for their utility for evolution experiments and remain underexploited. Here, we outline this experimental evolution work undertaken so far in Caenorhabditis, detail simple methodological tricks that can be exploited and identify research areas that are ripe for future discovery.

Utilizing population variation, vaccination, and systems biology to study human immunology

PubMed Central

Tsang, John S.

2016-01-01

The move toward precision medicine has highlighted the importance of understanding biological variability within and across individuals in the human population. In particular, given the prevalent involvement of the immune system in diverse pathologies, an important question is how much and what information about the state of the immune system is required to enable accurate prediction of future health and response to medical interventions. Towards addressing this question, recent studies using vaccination as a model perturbation and systems-biology approaches are beginning to provide a glimpse of how natural population variation together with multiplexed, high-throughput measurement and computational analysis can be used to uncover predictors of immune response quality in humans. Here I discuss recent developments in this emerging field, with emphasis on baseline correlates of vaccination responses, sources of immune-state variability, as well as relevant features of study design, data generation, and computational analysis. PMID:26187853

Next generation of network medicine: interdisciplinary signaling approaches.

PubMed

Korcsmaros, Tamas; Schneider, Maria Victoria; Superti-Furga, Giulio

2017-02-20

In the last decade, network approaches have transformed our understanding of biological systems. Network analyses and visualizations have allowed us to identify essential molecules and modules in biological systems, and improved our understanding of how changes in cellular processes can lead to complex diseases, such as cancer, infectious and neurodegenerative diseases. "Network medicine" involves unbiased large-scale network-based analyses of diverse data describing interactions between genes, diseases, phenotypes, drug targets, drug transport, drug side-effects, disease trajectories and more. In terms of drug discovery, network medicine exploits our understanding of the network connectivity and signaling system dynamics to help identify optimal, often novel, drug targets. Contrary to initial expectations, however, network approaches have not yet delivered a revolution in molecular medicine. In this review, we propose that a key reason for the limited impact, so far, of network medicine is a lack of quantitative multi-disciplinary studies involving scientists from different backgrounds. To support this argument, we present existing approaches from structural biology, 'omics' technologies (e.g., genomics, proteomics, lipidomics) and computational modeling that point towards how multi-disciplinary efforts allow for important new insights. We also highlight some breakthrough studies as examples of the potential of these approaches, and suggest ways to make greater use of the power of interdisciplinarity. This review reflects discussions held at an interdisciplinary signaling workshop which facilitated knowledge exchange from experts from several different fields, including in silico modelers, computational biologists, biochemists, geneticists, molecular and cell biologists as well as cancer biologists and pharmacologists.

Evolutionary game theory for physical and biological scientists. II. Population dynamics equations can be associated with interpretations

PubMed Central

Liao, David; Tlsty, Thea D.

2014-01-01

The use of mathematical equations to analyse population dynamics measurements is being increasingly applied to elucidate complex dynamic processes in biological systems, including cancer. Purely ‘empirical’ equations may provide sufficient accuracy to support predictions and therapy design. Nevertheless, interpretation of fitting equations in terms of physical and biological propositions can provide additional insights that can be used both to refine models that prove inconsistent with data and to understand the scope of applicability of models that validate. The purpose of this tutorial is to assist readers in mathematically associating interpretations with equations and to provide guidance in choosing interpretations and experimental systems to investigate based on currently available biological knowledge, techniques in mathematical and computational analysis and methods for in vitro and in vivo experiments. PMID:25097752

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

PubMed

Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique

2017-05-01

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

High School Students' Understanding of the Human Body System

ERIC Educational Resources Information Center

Assaraf, Orit Ben-Zvi; Dodick, Jeff; Tripto, Jaklin

2013-01-01

In this study, 120 tenth-grade students from 8 schools were examined to determine the extent of their ability to perceive the human body as a system after completing the first stage in their biology curriculum--"The human body, emphasizing homeostasis". The students' systems thinking was analyzed according to the STH thinking model, which roughly…

Systems biology in hepatology: approaches and applications.

PubMed

Mardinoglu, Adil; Boren, Jan; Smith, Ulf; Uhlen, Mathias; Nielsen, Jens

2018-06-01

Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

Towards molecular medicine: a case for a biological periodic table.

PubMed

Gawad, Charles

2005-01-01

The recently amplified pace of development in the technologies to study both normal and aberrant cellular physiology has allowed for a transition from the traditional reductionist approaches to global interrogations of human biology. This transformation has created the anticipation that we will soon more effectively treat or contain most types of diseases through a 'systems-based' approach to understanding and correcting the underlying etiology of these processes. However, to accomplish these goals, we must first have a more comprehensive understanding of all the elements involved in human cellular physiology, as well as why and how they interact. With the vast number of biological components that have and are being discovered, creating methods with modern computational techniques to better organize biological elements is the next requisite step in this process. This article aims to articulate the importance of the organization of chemical elements into a periodic table had on the conversion of chemistry into a quantitative, translatable science, as well as how we can apply the lessons learned in that transition to the current transformation taking place in biology.

Modifying patch-scale connectivity to initiate landscape change: An experimental approach to link scale

USDA-ARS?s Scientific Manuscript database

Nonlinear interactions and feedbacks across spatial and temporal scales are common features of biological and physical systems. These emergent behaviors often result in surprises that challenge the ability of scientists to understand and predict system behavior at one scale based on information at f...

CARBON AND NITROGEN ALLOCATION MODEL FOR THE SEAGRASS THALASSIA TESTUDUNUM IN LOWER LAGUNA MADRE

EPA Science Inventory

Inverse modeling methods are a powerful tool for understanding complex physiological relationships between seagrasses and their environment. The power of the method is a result of using ranges of data in a system of constraints to describe the biological system, in this case, t...

The Immune System Game

ERIC Educational Resources Information Center

Work, Kirsten A.; Gibbs, Melissa A.; Friedman, Erich J.

2015-01-01

We describe a card game that helps introductory biology students understand the basics of the immune response to pathogens. Students simulate the steps of the immune response with cards that represent the pathogens and the cells and molecules mobilized by the immune system. In the process, they learn the similarities and differences between the…

Effects of stress on endocrine and metabolic processes and redirection: Crosstalk between subcellular compartments

USDA-ARS?s Scientific Manuscript database

Recent advances in genome analysis and biochemical pathway mapping have advanced our understanding of how biological systems have evolved over time. Protein and DNA marker comparisons suggest that several of these systems are both ancient in origin but highly conserved into today’s evolved species. ...

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods.

PubMed

Gabanyi, Margaret J; Adams, Paul D; Arnold, Konstantin; Bordoli, Lorenza; Carter, Lester G; Flippen-Andersen, Judith; Gifford, Lida; Haas, Juergen; Kouranov, Andrei; McLaughlin, William A; Micallef, David I; Minor, Wladek; Shah, Raship; Schwede, Torsten; Tao, Yi-Ping; Westbrook, John D; Zimmerman, Matthew; Berman, Helen M

2011-07-01

The Protein Structure Initiative's Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org ) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI's high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology.

Systems Biology to Support Nanomaterial Grouping.

PubMed

Riebeling, Christian; Jungnickel, Harald; Luch, Andreas; Haase, Andrea

2017-01-01

The assessment of potential health risks of engineered nanomaterials (ENMs) is a challenging task due to the high number and great variety of already existing and newly emerging ENMs. Reliable grouping or categorization of ENMs with respect to hazards could help to facilitate prioritization and decision making for regulatory purposes. The development of grouping criteria, however, requires a broad and comprehensive data basis. A promising platform addressing this challenge is the systems biology approach. The different areas of systems biology, most prominently transcriptomics, proteomics and metabolomics, each of which provide a wealth of data that can be used to reveal novel biomarkers and biological pathways involved in the mode-of-action of ENMs. Combining such data with classical toxicological data would enable a more comprehensive understanding and hence might lead to more powerful and reliable prediction models. Physico-chemical data provide crucial information on the ENMs and need to be integrated, too. Overall statistical analysis should reveal robust grouping and categorization criteria and may ultimately help to identify meaningful biomarkers and biological pathways that sufficiently characterize the corresponding ENM subgroups. This chapter aims to give an overview on the different systems biology technologies and their current applications in the field of nanotoxicology, as well as to identify the existing challenges.

Metabolomic Analysis in Heart Failure.

PubMed

Ikegami, Ryutaro; Shimizu, Ippei; Yoshida, Yohko; Minamino, Tohru

2017-12-25

It is thought that at least 6,500 low-molecular-weight metabolites exist in humans, and these metabolites have various important roles in biological systems in addition to proteins and genes. Comprehensive assessment of endogenous metabolites is called metabolomics, and recent advances in this field have enabled us to understand the critical role of previously unknown metabolites or metabolic pathways in the cardiovascular system. In this review, we will focus on heart failure and how metabolomic analysis has contributed to improving our understanding of the pathogenesis of this critical condition.

Mammalian Synthetic Biology: Engineering Biological Systems.

PubMed

Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A

2017-06-21

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

Rewiring cells: synthetic biology as a tool to interrogate the organizational principles of living systems.

PubMed

Bashor, Caleb J; Horwitz, Andrew A; Peisajovich, Sergio G; Lim, Wendell A

2010-01-01

The living cell is an incredibly complex entity, and the goal of predictively and quantitatively understanding its function is one of the next great challenges in biology. Much of what we know about the cell concerns its constituent parts, but to a great extent we have yet to decode how these parts are organized to yield complex physiological function. Classically, we have learned about the organization of cellular networks by disrupting them through genetic or chemical means. The emerging discipline of synthetic biology offers an additional, powerful approach to study systems. By rearranging the parts that comprise existing networks, we can gain valuable insight into the hierarchical logic of the networks and identify the modular building blocks that evolution uses to generate innovative function. In addition, by building minimal toy networks, one can systematically explore the relationship between network structure and function. Here, we outline recent work that uses synthetic biology approaches to investigate the organization and function of cellular networks, and describe a vision for a synthetic biology toolkit that could be used to interrogate the design principles of diverse systems.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

How to Train a Cell - Cutting-Edge Molecular Tools

NASA Astrophysics Data System (ADS)

Czapiński, Jakub; Kiełbus, Michał; Kałafut, Joanna; Kos, Michał; Stepulak, Andrzej; Rivero-Müller, Adolfo

2017-03-01

In biological systems, the formation of molecular complexes is the currency for all cellular processes. Traditionally, functional experimentation was targeted to single molecular players in order to understand its effects in a cell or animal phenotype. In the last few years, we have been experiencing rapid progress in the development of ground-breaking molecular biology tools that affect the metabolic, structural, morphological, and (epi)genetic instructions of cells by chemical, optical (optogenetic) and mechanical inputs. Such precise dissection of cellular processes is not only essential for a better understanding of biological systems, but will also allow us to better diagnose and fix common dysfunctions. Here, we present several of these emerging and innovative techniques by providing the reader with elegant examples on how these tools have been implemented in cells, and, in some cases, organisms, to unravel molecular processes in minute detail. We also discuss their advantages and disadvantages with particular focus on their translation to multicellular organisms for in vivo spatiotemporal regulation. We envision that further developments of these tools will not only help solve the processes of life, but will give rise to novel clinical and industrial applications.

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

USGS Publications Warehouse

D'Erchia, Frank; Getter, James; D'Erchia, Terry D.; Root, Ralph; Stitt, Susan; White, Barbara

1998-01-01

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach.

PubMed

van Roekel, Hendrik W H; Rosier, Bas J H M; Meijer, Lenny H H; Hilbers, Peter A J; Markvoort, Albert J; Huck, Wilhelm T S; de Greef, Tom F A

2015-11-07

Living cells are able to produce a wide variety of biological responses when subjected to biochemical stimuli. It has become apparent that these biological responses are regulated by complex chemical reaction networks (CRNs). Unravelling the function of these circuits is a key topic of both systems biology and synthetic biology. Recent progress at the interface of chemistry and biology together with the realisation that current experimental tools are insufficient to quantitatively understand the molecular logic of pathways inside living cells has triggered renewed interest in the bottom-up development of CRNs. This builds upon earlier work of physical chemists who extensively studied inorganic CRNs and showed how a system of chemical reactions can give rise to complex spatiotemporal responses such as oscillations and pattern formation. Using purified biochemical components, in vitro synthetic biologists have started to engineer simplified model systems with the goal of mimicking biological responses of intracellular circuits. Emulation and reconstruction of system-level properties of intracellular networks using simplified circuits are able to reveal key design principles and molecular programs that underlie the biological function of interest. In this Tutorial Review, we present an accessible overview of this emerging field starting with key studies on inorganic CRNs followed by a discussion of recent work involving purified biochemical components. Finally, we review recent work showing the versatility of programmable biochemical reaction networks (BRNs) in analytical and diagnostic applications.

Robust mechanobiological behavior emerges in heterogeneous myosin systems.

PubMed

Egan, Paul F; Moore, Jeffrey R; Ehrlicher, Allen J; Weitz, David A; Schunn, Christian; Cagan, Jonathan; LeDuc, Philip

2017-09-26

Biological complexity presents challenges for understanding natural phenomenon and engineering new technologies, particularly in systems with molecular heterogeneity. Such complexity is present in myosin motor protein systems, and computational modeling is essential for determining how collective myosin interactions produce emergent system behavior. We develop a computational approach for altering myosin isoform parameters and their collective organization, and support predictions with in vitro experiments of motility assays with α-actinins as molecular force sensors. The computational approach models variations in single myosin molecular structure, system organization, and force stimuli to predict system behavior for filament velocity, energy consumption, and robustness. Robustness is the range of forces where a filament is expected to have continuous velocity and depends on used myosin system energy. Myosin systems are shown to have highly nonlinear behavior across force conditions that may be exploited at a systems level by combining slow and fast myosin isoforms heterogeneously. Results suggest some heterogeneous systems have lower energy use near stall conditions and greater energy consumption when unloaded, therefore promoting robustness. These heterogeneous system capabilities are unique in comparison with homogenous systems and potentially advantageous for high performance bionanotechnologies. Findings open doors at the intersections of mechanics and biology, particularly for understanding and treating myosin-related diseases and developing approaches for motor molecule-based technologies.

Robust mechanobiological behavior emerges in heterogeneous myosin systems

NASA Astrophysics Data System (ADS)

Egan, Paul F.; Moore, Jeffrey R.; Ehrlicher, Allen J.; Weitz, David A.; Schunn, Christian; Cagan, Jonathan; LeDuc, Philip

2017-09-01

Biological complexity presents challenges for understanding natural phenomenon and engineering new technologies, particularly in systems with molecular heterogeneity. Such complexity is present in myosin motor protein systems, and computational modeling is essential for determining how collective myosin interactions produce emergent system behavior. We develop a computational approach for altering myosin isoform parameters and their collective organization, and support predictions with in vitro experiments of motility assays with α-actinins as molecular force sensors. The computational approach models variations in single myosin molecular structure, system organization, and force stimuli to predict system behavior for filament velocity, energy consumption, and robustness. Robustness is the range of forces where a filament is expected to have continuous velocity and depends on used myosin system energy. Myosin systems are shown to have highly nonlinear behavior across force conditions that may be exploited at a systems level by combining slow and fast myosin isoforms heterogeneously. Results suggest some heterogeneous systems have lower energy use near stall conditions and greater energy consumption when unloaded, therefore promoting robustness. These heterogeneous system capabilities are unique in comparison with homogenous systems and potentially advantageous for high performance bionanotechnologies. Findings open doors at the intersections of mechanics and biology, particularly for understanding and treating myosin-related diseases and developing approaches for motor molecule-based technologies.

Synthetic biology between technoscience and thing knowledge.

PubMed

Gelfert, Axel

2013-06-01

Synthetic biology presents a challenge to traditional accounts of biology: Whereas traditional biology emphasizes the evolvability, variability, and heterogeneity of living organisms, synthetic biology envisions a future of homogeneous, humanly engineered biological systems that may be combined in modular fashion. The present paper approaches this challenge from the perspective of the epistemology of technoscience. In particular, it is argued that synthetic-biological artifacts lend themselves to an analysis in terms of what has been called 'thing knowledge'. As such, they should neither be regarded as the simple outcome of applying theoretical knowledge and engineering principles to specific technological problems, nor should they be treated as mere sources of new evidence in the general pursuit of scientific understanding. Instead, synthetic-biological artifacts should be viewed as partly autonomous research objects which, qua their material-biological constitution, embody knowledge about the natural world-knowledge that, in turn, can be accessed via continuous experimental interrogation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Enhancement of COPD biological networks using a web-based collaboration interface

PubMed Central

Boue, Stephanie; Fields, Brett; Hoeng, Julia; Park, Jennifer; Peitsch, Manuel C.; Schlage, Walter K.; Talikka, Marja; Binenbaum, Ilona; Bondarenko, Vladimir; Bulgakov, Oleg V.; Cherkasova, Vera; Diaz-Diaz, Norberto; Fedorova, Larisa; Guryanova, Svetlana; Guzova, Julia; Igorevna Koroleva, Galina; Kozhemyakina, Elena; Kumar, Rahul; Lavid, Noa; Lu, Qingxian; Menon, Swapna; Ouliel, Yael; Peterson, Samantha C.; Prokhorov, Alexander; Sanders, Edward; Schrier, Sarah; Schwaitzer Neta, Golan; Shvydchenko, Irina; Tallam, Aravind; Villa-Fombuena, Gema; Wu, John; Yudkevich, Ilya; Zelikman, Mariya

2015-01-01

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks. PMID:25767696

Enhancement of COPD biological networks using a web-based collaboration interface.

PubMed

Boue, Stephanie; Fields, Brett; Hoeng, Julia; Park, Jennifer; Peitsch, Manuel C; Schlage, Walter K; Talikka, Marja; Binenbaum, Ilona; Bondarenko, Vladimir; Bulgakov, Oleg V; Cherkasova, Vera; Diaz-Diaz, Norberto; Fedorova, Larisa; Guryanova, Svetlana; Guzova, Julia; Igorevna Koroleva, Galina; Kozhemyakina, Elena; Kumar, Rahul; Lavid, Noa; Lu, Qingxian; Menon, Swapna; Ouliel, Yael; Peterson, Samantha C; Prokhorov, Alexander; Sanders, Edward; Schrier, Sarah; Schwaitzer Neta, Golan; Shvydchenko, Irina; Tallam, Aravind; Villa-Fombuena, Gema; Wu, John; Yudkevich, Ilya; Zelikman, Mariya

2015-01-01

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks.

Programming Morphogenesis through Systems and Synthetic Biology.

PubMed

Velazquez, Jeremy J; Su, Emily; Cahan, Patrick; Ebrahimkhani, Mo R

2018-04-01

Mammalian tissue development is an intricate, spatiotemporal process of self-organization that emerges from gene regulatory networks of differentiating stem cells. A major goal in stem cell biology is to gain a sufficient understanding of gene regulatory networks and cell-cell interactions to enable the reliable and robust engineering of morphogenesis. Here, we review advances in synthetic biology, single cell genomics, and multiscale modeling, which, when synthesized, provide a framework to achieve the ambitious goal of programming morphogenesis in complex tissues and organoids. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structural Bioinformatics of the Interactome

PubMed Central

Petrey, Donald; Honig, Barry

2014-01-01

The last decade has seen a dramatic expansion in the number and range of techniques available to obtain genome-wide information, and to analyze this information so as to infer both the function of individual molecules and how they interact to modulate the behavior of biological systems. Here we review these techniques, focusing on the construction of physical protein-protein interaction networks, and highlighting approaches that incorporate protein structure which is becoming an increasingly important component of systems-level computational techniques. We also discuss how network analyses are being applied to enhance the basic understanding of biological systems and their disregulation, and how they are being applied in drug development. PMID:24895853

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

Investigating Processes of Materials Formation via Liquid Phase and Cryogenic TEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Yoreo, James J.; Sommerdijk, Nico

2016-06-14

The formation of materials in solutions is a widespread phenomenon in synthetic, biological and geochemical systems, occurring through dynamic processes of nucleation, self-assembly, crystal growth, and coarsening. The recent advent of liquid phase TEM and advances in cryogenic TEM are transforming our understanding of these phenomena by providing new insights into the underlying physical and chemical mechanisms. The techniques have been applied to metallic and semiconductor nanoparticles, geochemical and biological minerals, electrochemical systems, macromolecular complexes, and selfassembling systems, both organic and inorganic. New instrumentation and methodologies currently on the horizon promise new opportunities for advancing the science of materials synthesis.

Simbios: an NIH national center for physics-based simulation of biological structures.

PubMed

Delp, Scott L; Ku, Joy P; Pande, Vijay S; Sherman, Michael A; Altman, Russ B

2012-01-01

Physics-based simulation provides a powerful framework for understanding biological form and function. Simulations can be used by biologists to study macromolecular assemblies and by clinicians to design treatments for diseases. Simulations help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, synthetic tissues, medical devices, and surgical interventions. Although individual biomedical investigators make outstanding contributions to physics-based simulation, the field has been fragmented. Applications are typically limited to a single physical scale, and individual investigators usually must create their own software. These conditions created a major barrier to advancing simulation capabilities. In 2004, we established a National Center for Physics-Based Simulation of Biological Structures (Simbios) to help integrate the field and accelerate biomedical research. In 6 years, Simbios has become a vibrant national center, with collaborators in 16 states and eight countries. Simbios focuses on problems at both the molecular scale and the organismal level, with a long-term goal of uniting these in accurate multiscale simulations.

Simulating the bio nanoelectronic interface

NASA Astrophysics Data System (ADS)

Millar, Campbell; Roy, Scott; Brown, Andrew R.; Asenov, Asen

2007-05-01

As the size of conventional nano-CMOS devices continues to shrink, they are beginning to approach the size of biologically relevant macromolecules such as ion channels. This, in concert with the increasing understanding of the behaviour of proteins in vivo, creates the potential for a revolution in the sensing, measurement and interaction with biological systems. In this paper we will demonstrate the theoretical possibility of directly coupling a nanoscale MOSFET with a model ion channel protein. This will potentially allow a much better understanding of the behaviour of biologically relevant molecules, since the measurement of the motion of charged particles can reveal a substantial amount of information about protein structure-function relationships. We can use the MOSFET's innate sensitivity to stray charge to detect the positions of single ions and, thus, better explore the dynamics of ion conduction in channel proteins. In addition, we also demonstrate that the MOSFET can be 'tuned' to sense current flow through channel proteins, thus providing, for the first time, a direct solid state/biological interface at the atomic level.

Expectancies as core features of mental disorders.

PubMed

Rief, Winfried; Glombiewski, Julia A; Gollwitzer, Mario; Schubö, Anna; Schwarting, Rainer; Thorwart, Anna

2015-09-01

Expectancies are core features of mental disorders, and change in expectations is therefore one of the core mechanisms of treatment in psychiatry. We aim to improve our understanding of expectancies by summarizing factors that contribute to their development, persistence, and modification. We pay particular attention to the issue of persistence of expectancies despite experiences that contradict them. Based on recent research findings, we propose a new model for expectation persistence and expectation change. When expectations are established, effects are evident in neural and other biological systems, for example, via anticipatory reactions, different biological reactions to expected versus unexpected stimuli, etc. Psychological 'immunization' and 'assimilation', implicit self-confirming processes, and stability of biological processes help us to better understand why expectancies persist even in the presence of expectation violations. Learning theory, attentional processes, social influences, and biological determinants contribute to the development, persistence, and modification of expectancies. Psychological interventions should focus on optimizing expectation violation to achieve optimal treatment outcome and to avoid treatment failures.

Simbios: an NIH national center for physics-based simulation of biological structures

PubMed Central

Delp, Scott L; Ku, Joy P; Pande, Vijay S; Sherman, Michael A

2011-01-01

Physics-based simulation provides a powerful framework for understanding biological form and function. Simulations can be used by biologists to study macromolecular assemblies and by clinicians to design treatments for diseases. Simulations help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, synthetic tissues, medical devices, and surgical interventions. Although individual biomedical investigators make outstanding contributions to physics-based simulation, the field has been fragmented. Applications are typically limited to a single physical scale, and individual investigators usually must create their own software. These conditions created a major barrier to advancing simulation capabilities. In 2004, we established a National Center for Physics-Based Simulation of Biological Structures (Simbios) to help integrate the field and accelerate biomedical research. In 6 years, Simbios has become a vibrant national center, with collaborators in 16 states and eight countries. Simbios focuses on problems at both the molecular scale and the organismal level, with a long-term goal of uniting these in accurate multiscale simulations. PMID:22081222

Bridging the physical scales in evolutionary biology: From protein sequence space to fitness of organisms and populations

PubMed Central

Bershtein, Shimon; Serohijos, Adrian W.R.; Shakhnovich, Eugene I.

2016-01-01

Bridging the gap between the molecular properties of proteins and organismal/population fitness is essential for understanding evolutionary processes. This task requires the integration of the several physical scales of biological organization, each defined by a distinct set of mechanisms and constraints, into a single unifying model. The molecular scale is dominated by the constraints imposed by the physico-chemical properties of proteins and their substrates, which give rise to trade-offs and epistatic (non-additive) effects of mutations. At the systems scale, biological networks modulate protein expression and can either buffer or enhance the fitness effects of mutations. The population scale is influenced by the mutational input, selection regimes, and stochastic changes affecting the size and structure of populations, which eventually determine the evolutionary fate of mutations. Here, we summarize the recent advances in theory, computer simulations, and experiments that advance our understanding of the links between various physical scales in biology. PMID:27810574

Bridging the physical scales in evolutionary biology: from protein sequence space to fitness of organisms and populations.

PubMed

Bershtein, Shimon; Serohijos, Adrian Wr; Shakhnovich, Eugene I

2017-02-01

Bridging the gap between the molecular properties of proteins and organismal/population fitness is essential for understanding evolutionary processes. This task requires the integration of the several physical scales of biological organization, each defined by a distinct set of mechanisms and constraints, into a single unifying model. The molecular scale is dominated by the constraints imposed by the physico-chemical properties of proteins and their substrates, which give rise to trade-offs and epistatic (non-additive) effects of mutations. At the systems scale, biological networks modulate protein expression and can either buffer or enhance the fitness effects of mutations. The population scale is influenced by the mutational input, selection regimes, and stochastic changes affecting the size and structure of populations, which eventually determine the evolutionary fate of mutations. Here, we summarize the recent advances in theory, computer simulations, and experiments that advance our understanding of the links between various physical scales in biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bacteriophage-based synthetic biology for the study of infectious diseases

PubMed Central

Lu, Timothy K.

2014-01-01

Since their discovery, bacteriophages have contributed enormously to our understanding of molecular biology as model systems. Furthermore, bacteriophages have provided many tools that have advanced the fields of genetic engineering and synthetic biology. Here, we discuss bacteriophage-based technologies and their application to the study of infectious diseases. New strategies for engineering genomes have the potential to accelerate the design of novel phages as therapies, diagnostics, and tools. Though almost a century has elapsed since their discovery, bacteriophages continue to have a major impact on modern biological sciences, especially with the growth of multidrug-resistant bacteria and interest in the microbiome. PMID:24997401

Understanding the Role of Biology in the Global Environment: NASA'S Mission to Planet Earth

NASA Technical Reports Server (NTRS)

Townsend, William F.

1996-01-01

NASA has long used the unique perspective of space as a means of expanding our understanding of how the Earth's environment functions. In particular, the linkages between land, air, water, and life-the elements of the Earth system-are a focus for NASA's Mission to Planet Earth. This approach, called Earth system science, blends together fields like meteorology, biology, oceanography, and atmospheric science. Mission to Planet Earth uses observations from satellites, aircraft, balloons, and ground researchers as the basis for analysis of the elements of the Earth system, the interactions between those elements, and possible changes over the coming years and decades. This information is helping scientists improve our understanding of how natural processes affect us and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, an enhanced ability to predict how the climate will change in the future. NASA has designed Mission to Planet Earth to focus on five primary themes: Land Cover and Land Use Change; Seasonal to Interannual Climate Prediction; Natural Hazards; Long-Term Climate Variability; and Atmosphere Ozone.

Abasy Atlas: a comprehensive inventory of systems, global network properties and systems-level elements across bacteria

PubMed Central

Ibarra-Arellano, Miguel A.; Campos-González, Adrián I.; Treviño-Quintanilla, Luis G.; Tauch, Andreas; Freyre-González, Julio A.

2016-01-01

The availability of databases electronically encoding curated regulatory networks and of high-throughput technologies and methods to discover regulatory interactions provides an invaluable source of data to understand the principles underpinning the organization and evolution of these networks responsible for cellular regulation. Nevertheless, data on these sources never goes beyond the regulon level despite the fact that regulatory networks are complex hierarchical-modular structures still challenging our understanding. This brings the necessity for an inventory of systems across a large range of organisms, a key step to rendering feasible comparative systems biology approaches. In this work, we take the first step towards a global understanding of the regulatory networks organization by making a cartography of the functional architectures of diverse bacteria. Abasy (Across-bacteria systems) Atlas provides a comprehensive inventory of annotated functional systems, global network properties and systems-level elements (global regulators, modular genes shaping functional systems, basal machinery genes and intermodular genes) predicted by the natural decomposition approach for reconstructed and meta-curated regulatory networks across a large range of bacteria, including pathogenically and biotechnologically relevant organisms. The meta-curation of regulatory datasets provides the most complete and reliable set of regulatory interactions currently available, which can even be projected into subsets by considering the force or weight of evidence supporting them or the systems that they belong to. Besides, Abasy Atlas provides data enabling large-scale comparative systems biology studies aimed at understanding the common principles and particular lifestyle adaptions of systems across bacteria. Abasy Atlas contains systems and system-level elements for 50 regulatory networks comprising 78 649 regulatory interactions covering 42 bacteria in nine taxa, containing 3708 regulons and 1776 systems. All this brings together a large corpus of data that will surely inspire studies to generate hypothesis regarding the principles governing the evolution and organization of systems and the functional architectures controlling them. Database URL: http://abasy.ccg.unam.mx PMID:27242034

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Positive affect and psychobiological processes

PubMed Central

Dockray, Samantha; Steptoe, Andrew

2010-01-01

Positive affect has been associated with favourable health outcomes, and it is likely that several biological processes mediate the effects of positive mood on physical health. There is converging evidence that positive affect activates the neuroendocrine, autonomic and immune systems in distinct and functionally meaningful ways. Cortisol, both total output and the awakening response, has consistently been shown to be lower among individuals with higher levels of positive affect. The beneficial effects of positive mood on cardiovascular function, including heart rate and blood pressure, and the immune system have also been described. The influence of positive affect on these psychobiological processes are independent of negative affect, suggesting that positive affect may have characteristic biological correlates. The duration and conceptualisation of positive affect may be important considerations in understanding how different biological systems are activated in association with positive affect. The association of positive affect and psychobiological processes has been established, and these biological correlates may be partly responsible for the protective effects of positive affect on health outcomes. PMID:20097225

A Computational Framework for Bioimaging Simulation.

PubMed

Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

Biological effects of exposure to magnetic resonance imaging: an overview

PubMed Central

Formica, Domenico; Silvestri, Sergio

2004-01-01

The literature on biological effects of magnetic and electromagnetic fields commonly utilized in magnetic resonance imaging systems is surveyed here. After an introduction on the basic principles of magnetic resonance imaging and the electric and magnetic properties of biological tissues, the basic phenomena to understand the bio-effects are described in classical terms. Values of field strengths and frequencies commonly utilized in these diagnostic systems are reported in order to allow the integration of the specific literature on the bio-effects produced by magnetic resonance systems with the vast literature concerning the bio-effects produced by electromagnetic fields. This work gives an overview of the findings about the safety concerns of exposure to static magnetic fields, radio-frequency fields, and time varying magnetic field gradients, focusing primarily on the physics of the interactions between these electromagnetic fields and biological matter. The scientific literature is summarized, integrated, and critically analyzed with the help of authoritative reviews by recognized experts, international safety guidelines are also cited. PMID:15104797

Investigating the Effectiveness of an Inquiry-Based Intervention on Human Reproduction in Relation to Students' Gender, Prior Knowledge and Motivation for Learning in Biology

ERIC Educational Resources Information Center

Hadjichambis, Andreas Ch.; Georgiou, Yiannis; Paraskeva-Hadjichambi, Demetra; Kyza, Eleni A.; Mappouras, Demetrios

2016-01-01

Despite the importance of understanding how the human reproductive system works, adolescents worldwide exhibit weak conceptual understanding, which leads to serious risks, such as unwanted pregnancies and sexually transmitted diseases. Studies focusing on the development and evaluation of inquiry-based learning interventions, promoting the…

The Lymphatic System and Pancreatic Cancer

PubMed Central

Fink, Darci M.; Steele, Maria M.; Hollingsworth, Michael A.

2016-01-01

This review summarizes current knowledge of the biology, pathology and clinical understanding of lymphatic invasion and metastasis in pancreatic cancer. We discuss the clinical and biological consequences of lymphatic invasion and metastasis, including paraneoplastic effects on immune responses and consider the possible benefit of therapies to treat tumors that are localized to lymphatics. A review of current techniques and methods to study interactions between tumors and lymphatics is presented. PMID:26742462

The principle of sufficiency and the evolution of control: using control analysis to understand the design principles of biological systems.

PubMed

Brown, Guy C

2010-10-01

Control analysis can be used to try to understand why (quantitatively) systems are the way that they are, from rate constants within proteins to the relative amount of different tissues in organisms. Many biological parameters appear to be optimized to maximize rates under the constraint of minimizing space utilization. For any biological process with multiple steps that compete for control in series, evolution by natural selection will tend to even out the control exerted by each step. This is for two reasons: (i) shared control maximizes the flux for minimum protein concentration, and (ii) the selection pressure on any step is proportional to its control, and selection will, by increasing the rate of a step (relative to other steps), decrease its control over a pathway. The control coefficient of a parameter P over fitness can be defined as (∂N/N)/(∂P/P), where N is the number of individuals in the population, and ∂N is the change in that number as a result of the change in P. This control coefficient is equal to the selection pressure on P. I argue that biological systems optimized by natural selection will conform to a principle of sufficiency, such that the control coefficient of all parameters over fitness is 0. Thus in an optimized system small changes in parameters will have a negligible effect on fitness. This principle naturally leads to (and is supported by) the dominance of wild-type alleles over null mutants.

Ecology and evolution of plant–pollinator interactions

PubMed Central

Mitchell, Randall J.; Irwin, Rebecca E.; Flanagan, Rebecca J.; Karron, Jeffrey D.

2009-01-01

Background Some of the most exciting advances in pollination biology have resulted from interdisciplinary research combining ecological and evolutionary perspectives. For example, these two approaches have been essential for understanding the functional ecology of floral traits, the dynamics of pollen transport, competition for pollinator services, and patterns of specialization and generalization in plant–pollinator interactions. However, as research in these and other areas has progressed, many pollination biologists have become more specialized in their research interests, focusing their attention on either evolutionary or ecological questions. We believe that the continuing vigour of a synthetic and interdisciplinary field like pollination biology depends on renewed connections between ecological and evolutionary approaches. Scope In this Viewpoint paper we highlight the application of ecological and evolutionary approaches to two themes in pollination biology: (1) links between pollinator behaviour and plant mating systems, and (2) generalization and specialization in pollination systems. We also describe how mathematical models and synthetic analyses have broadened our understanding of pollination biology, especially in human-modified landscapes. We conclude with several suggestions that we hope will stimulate future research. This Viewpoint also serves as the introduction to this Special Issue on the Ecology and Evolution of Plant–Pollinator Interactions. These papers provide inspiring examples of the synergy between evolutionary and ecological approaches, and offer glimpses of great accomplishments yet to come. PMID:19482881

Ecology and evolution of plant-pollinator interactions.

PubMed

Mitchell, Randall J; Irwin, Rebecca E; Flanagan, Rebecca J; Karron, Jeffrey D

2009-06-01

Some of the most exciting advances in pollination biology have resulted from interdisciplinary research combining ecological and evolutionary perspectives. For example, these two approaches have been essential for understanding the functional ecology of floral traits, the dynamics of pollen transport, competition for pollinator services, and patterns of specialization and generalization in plant-pollinator interactions. However, as research in these and other areas has progressed, many pollination biologists have become more specialized in their research interests, focusing their attention on either evolutionary or ecological questions. We believe that the continuing vigour of a synthetic and interdisciplinary field like pollination biology depends on renewed connections between ecological and evolutionary approaches. In this Viewpoint paper we highlight the application of ecological and evolutionary approaches to two themes in pollination biology: (1) links between pollinator behaviour and plant mating systems, and (2) generalization and specialization in pollination systems. We also describe how mathematical models and synthetic analyses have broadened our understanding of pollination biology, especially in human-modified landscapes. We conclude with several suggestions that we hope will stimulate future research. This Viewpoint also serves as the introduction to this Special Issue on the Ecology and Evolution of Plant-Pollinator Interactions. These papers provide inspiring examples of the synergy between evolutionary and ecological approaches, and offer glimpses of great accomplishments yet to come.

Formal reasoning about systems biology using theorem proving

PubMed Central

Hasan, Osman; Siddique, Umair; Tahar, Sofiène

2017-01-01

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients. PMID:28671950

Using insects to drive mobile robots - hybrid robots bridge the gap between biological and artificial systems.

PubMed

Ando, Noriyasu; Kanzaki, Ryohei

2017-09-01

The use of mobile robots is an effective method of validating sensory-motor models of animals in a real environment. The well-identified insect sensory-motor systems have been the major targets for modeling. Furthermore, mobile robots implemented with such insect models attract engineers who aim to avail advantages from organisms. However, directly comparing the robots with real insects is still difficult, even if we successfully model the biological systems, because of the physical differences between them. We developed a hybrid robot to bridge the gap. This hybrid robot is an insect-controlled robot, in which a tethered male silkmoth (Bombyx mori) drives the robot in order to localize an odor source. This robot has the following three advantages: 1) from a biomimetic perspective, the robot enables us to evaluate the potential performance of future insect-mimetic robots; 2) from a biological perspective, the robot enables us to manipulate the closed-loop of an onboard insect for further understanding of its sensory-motor system; and 3) the robot enables comparison with insect models as a reference biological system. In this paper, we review the recent works regarding insect-controlled robots and discuss the significance for both engineering and biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Environmental stressors influencing hormones and systems physiology in cattle

PubMed Central

2014-01-01

Environmental stressors undoubtedly influence organismal biology, specifically the endocrine system that, in turn, impact cattle at the systems physiology level. Despite the significant advances in understanding the genetic determinants of the ideal dairy or beef cow, there is a grave lack of understanding of the systems physiology and effects of the environmental stressors that interfere with the endocrine system. This is a major problem because the lack of such knowledge is preventing advances in understanding gene-environment interactions and developing science-based solutions to these challenges. In this review, we synthesize the current knowledge on the nature of the major environmental stressors, such as climate (heat, cold, wind, and humidity), nutrition (feeds, feeding systems, and endocrine disruptors) and management (housing density and conditions, transportation, weaning practices). We summarize the impact of each one of these factors on cattle at the systems level, and provide solutions for the challenges. PMID:24996419

Ecosystem function in waste stabilisation ponds: Improving water quality through a better understanding of biophysical coupling

NASA Astrophysics Data System (ADS)

Ghadouani, Anas; Reichwaldt, Elke S.; Coggins, Liah X.; Ivey, Gregory N.; Ghisalberti, Marco; Zhou, Wenxu; Laurion, Isabelle; Chua, Andrew

2014-05-01

Wastewater stabilisation ponds (WSPs) are highly productive systems designed to treat wastewater using only natural biological and chemical processes. Phytoplankton, microbial communities and hydraulics play important roles for ecosystem functionality of these pond systems. Although WSPs have been used for many decades, they are still considered as 'black box' systems as very little is known about the fundamental ecological processes which occur within them. However, a better understanding of how these highly productive ecosystems function is particularly important for hydrological processes, as treated wastewater is commonly discharged into streams, rivers, and oceans, and subject to strict water quality guidelines. WSPs are known to operate at different levels of efficiency, and treatment efficiency of WSPs is dependent on physical (flow characteristics and sludge accumulation and distribution) and biological (microbial and phytoplankton communities) characteristics. Thus, it is important to gain a better understanding of the role and influence of pond hydraulics and vital microbial communities on pond performance and WSP functional stability. The main aim of this study is to investigate the processes leading to differences in treatment performance of WSPs. This study uses a novel and innovative approach to understand these factors by combining flow cytometry and metabolomics to investigate various biochemical characteristics, including the metabolite composition and microbial community within WSPs. The results of these analyses will then be combined with results from the characterisation of pond hydrodynamics and hydraulic performance, which will be performed using advanced hydrodynamic modelling and advanced sludge profiling technology. By understanding how hydrodynamic and biological processes influence each other and ecosystem function and stability in WSPs, we will be able to propose ways to improve the quality of the treatment using natural processes, with less reliance on chemical treatment. This will in turn contribute to the reduction in the cost of operation, but more importantly reduce the impact on the environment (i.e., discharge, GHGs), and increase water quality and the potential for water reuse worldwide.

Computational intelligence approaches for pattern discovery in biological systems.

PubMed

Fogel, Gary B

2008-07-01

Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.

Controlled biological and biomimetic systems for landmine detection.

PubMed

Habib, Maki K

2007-08-30

Humanitarian demining requires to accurately detect, locate and deactivate every single landmine and other buried mine-like objects as safely and as quickly as possible, and in the most non-invasive manner. The quality of landmine detection affects directly the efficiency and safety of this process. Most of the available methods to detect explosives and landmines are limited by their sensitivity and/or operational complexities. All landmines leak with time small amounts of their explosives that can be found on surrounding ground and plant life. Hence, explosive signatures represent the robust primary indicator of landmines. Accordingly, developing innovative technologies and efficient techniques to identify in real-time explosives residue in mined areas represents an attractive and promising approach. Biological and biologically inspired detection technology has the potential to compete with or be used in conjunction with other artificial technology to complement performance strengths. Biological systems are sensitive to many different scents concurrently, a property that has proven difficult to replicate artificially. Understanding biological systems presents unique opportunities for developing new capabilities through direct use of trained bio-systems, integration of living and non-living components, or inspiring new design by mimicking biological capabilities. It is expected that controlled bio-systems, biotechnology and microbial techniques will contribute to the advancement of mine detection and other application domains. This paper provides directions, evaluation and analysis on the progress of controlled biological and biomimetic systems for landmine detection. It introduces and discusses different approaches developed, underlining their relative advantages and limitations, and highlighting trends, safety and ecology concern, and possible future directions.

Role of the neural niche in brain metastatic cancer

PubMed Central

Termini, John; Neman, Josh; Jandial, Rahul

2014-01-01

Metastasis is the relenteless pursuit of cancer to escape its primary site and colonize distant organs. This malignant evolutionary process is biologically heterogeneous, yet one unifying element is the critical role of the microenvironment for arriving metastatic cells. Historically brain metastases were rarely investigated since patients with advanced cancer were considered terminal. Fortunately, advances in molecular therapies have led to patients living longer with metastatic cancer. However, one site remains recalcitrant to our treatment efforts – the brain. The central nervous system is the most complex biological system, which poses unique obstacles but also harbors opportunities for discovery. Much of what we know about the brain microenvironment comes from neuroscience. We suggest that the interrelated cellular responses in traumatic brain injury may guide us towards new perspectives in understanding brain metastases. In this view, brain metastases may be conceptualized as progressive oncologic injury to the nervous system. This review discusses our evolving understanding of the bidirectional interactions between the brain milieu and metastatic cancer. PMID:25035392

Role of the neural niche in brain metastatic cancer.

PubMed

Termini, John; Neman, Josh; Jandial, Rahul

2014-08-01

Metastasis is the relentless pursuit of cancer to escape its primary site and colonize distant organs. This malignant evolutionary process is biologically heterogeneous, yet one unifying element is the critical role of the microenvironment for arriving metastatic cells. Historically, brain metastases were rarely investigated because patients with advanced cancer were considered terminal. Fortunately, advances in molecular therapies have led to patients living longer with metastatic cancer. However, one site remains recalcitrant to our treatment efforts, the brain. The central nervous system is the most complex biologic system, which poses unique obstacles but also harbors opportunities for discovery. Much of what we know about the brain microenvironment comes from neuroscience. We suggest that the interrelated cellular responses in traumatic brain injury may guide us toward new perspectives in understanding brain metastases. In this view, brain metastases may be conceptualized as progressive oncologic injury to the nervous system. This review discusses our evolving understanding of bidirectional interactions between the brain milieu and metastatic cancer. ©2014 American Association for Cancer Research.

The Intersection of Theory and Application in Elucidating Pattern Formation in Developmental Biology

PubMed Central

Othmer, Hans G.; Painter, Kevin; Umulis, David; Xue, Chuan

2009-01-01

We discuss theoretical and experimental approaches to three distinct developmental systems that illustrate how theory can influence experimental work and vice-versa. The chosen systems – Drosophila melanogaster, bacterial pattern formation, and pigmentation patterns – illustrate the fundamental physical processes of signaling, growth and cell division, and cell movement involved in pattern formation and development. These systems exemplify the current state of theoretical and experimental understanding of how these processes produce the observed patterns, and illustrate how theoretical and experimental approaches can interact to lead to a better understanding of development. As John Bonner said long ago ‘We have arrived at the stage where models are useful to suggest experiments, and the facts of the experiments in turn lead to new and improved models that suggest new experiments. By this rocking back and forth between the reality of experimental facts and the dream world of hypotheses, we can move slowly toward a satisfactory solution of the major problems of developmental biology.’ PMID:19844610

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. Results We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. Conclusion We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis. PMID:18257938

A Tricky Trait: Applying the Fruits of the “Function Debate” in the Philosophy of Biology to the “Venom Debate” in the Science of Toxinology

PubMed Central

Jackson, Timothy N. W.; Fry, Bryan G.

2016-01-01

The “function debate” in the philosophy of biology and the “venom debate” in the science of toxinology are conceptually related. Venom systems are complex multifunctional traits that have evolved independently numerous times throughout the animal kingdom. No single concept of function, amongst those popularly defended, appears adequate to describe these systems in all their evolutionary contexts and extant variations. As such, a pluralistic view of function, previously defended by some philosophers of biology, is most appropriate. Venom systems, like many other functional traits, exist in nature as points on a continuum and the boundaries between “venomous” and “non-venomous” species may not always be clearly defined. This paper includes a brief overview of the concept of function, followed by in-depth discussion of its application to venom systems. A sound understanding of function may aid in moving the venom debate forward. Similarly, consideration of a complex functional trait such as venom may be of interest to philosophers of biology. PMID:27618098

Recent Advances in the Chemical Biology of Nitroxyl (HNO) Detection and Generation

PubMed Central

Miao, Zhengrui; King, S. Bruce

2016-01-01

Nitroxyl or azanone (HNO) represents the redox-related (one electron reduced and protonated) relative of the well-known biological signaling molecule nitric oxide (NO). Despite the close structural similarity to NO, defined biological roles and endogenous formation of HNO remain unclear due to the high reactivity of HNO with itself, soft nucleophiles and transition metals. While significant work has been accomplished in terms of the physiology, biology and chemistry of HNO, important and clarifying work regarding HNO detection and formation has occurred within the last 10 years. This review summarizes advances in the areas of HNO detection and donation and their application to normal and pathological biology. Such chemical biological tools allow a deeper understanding of biological HNO formation and the role that HNO plays in a variety of physiological systems. PMID:27108951

Ask not what physics can do for biology--ask what biology can do for physics.

PubMed

Frauenfelder, Hans

2014-10-08

Stan Ulam, the famous mathematician, said once to Hans Frauenfelder: 'Ask not what Physics can do for biology, ask what biology can do for physics'. The interaction between biologists and physicists is a two-way street. Biology reveals the secrets of complex systems, physics provides the physical tools and the theoretical concepts to understand the complexity. The perspective gives a personal view of the path to some of the physical concepts that are relevant for biology and physics (Frauenfelder et al 1999 Rev. Mod. Phys. 71 S419-S442). Schrödinger's book (Schrödinger 1944 What is Life? (Cambridge: Cambridge University Press)), loved by physicists and hated by eminent biologists (Dronamraju 1999 Genetics 153 1071-6), still shows how a great physicist looked at biology well before the first protein structure was known.

Next generation simulation tools: the Systems Biology Workbench and BioSPICE integration.

PubMed

Sauro, Herbert M; Hucka, Michael; Finney, Andrew; Wellock, Cameron; Bolouri, Hamid; Doyle, John; Kitano, Hiroaki

2003-01-01

Researchers in quantitative systems biology make use of a large number of different software packages for modelling, analysis, visualization, and general data manipulation. In this paper, we describe the Systems Biology Workbench (SBW), a software framework that allows heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' capabilities via a fast binary encoded-message system. Our goal was to create a simple, high performance, opensource software infrastructure which is easy to implement and understand. SBW enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe in this paper the SBW architecture, a selection of current modules, including Jarnac, JDesigner, and SBWMeta-tool, and the close integration of SBW into BioSPICE, which enables both frameworks to share tools and compliment and strengthen each others capabilities.

Balancing Broad Ideas with Context: An Evaluation of Student Accuracy in Describing Ecosystem Processes after a System-Level Intervention

ERIC Educational Resources Information Center

Jordan, Rebecca C.; Brooks, Wesley R.; Hmelo-Silver, Cindy; Eberbach, Catherine; Sinha, Suparna

2014-01-01

Promoting student understanding of ecosystem processes is critical to biological education. Yet, teaching complex life systems can be difficult because systems are dynamic and often behave in a non-linear manner. In this paper, we discuss assessment results from a middle school classroom intervention in which a conceptual representation framework…

Promoting Student Teachers' Content Related Knowledge in Teaching Systems Thinking: Measuring Effects of an Intervention through Evaluating a Videotaped Lesson

ERIC Educational Resources Information Center

Rosenkränzer, Frank; Kramer, Tim; Hörsch, Christian; Schuler, Stephan; Rieß, Werner

2016-01-01

The understanding of complex, dynamic and animate systems has a special standing in education for sustainable development and biology. Thus one important role of science teacher education is to promote student teachers' Content Related Knowledge (CRK) for teaching systems thinking, consisting of extensive Content Knowledge (CK) and well formed…

A blueprint for the synthesis and characterisation of thin graphene oxide with controlled lateral dimensions for biomedicine

NASA Astrophysics Data System (ADS)

Filipe Rodrigues, Artur; Newman, Leon; Lozano, Neus; Mukherjee, Sourav P.; Fadeel, Bengt; Bussy, Cyrill; Kostarelos, Kostas

2018-07-01

Graphene-based materials (GBMs) have ignited a revolution in material science and technology, with electronic, optical and mechanical properties that are of relevant interest for a wide range of applications. To support the development of these enabling technologies, a global research effort has been invested to assess their hazard and biocompatibility. Different production methods have however generated a diverse collection of GBMs with different physicochemical properties, leading to a variety of biological outcomes that are still not fully understood. To better understand the biological interactions of GBMs with biological systems and allow the design of safer materials, a thorough physicochemical characterisation is therefore highly recommended. The aim of the present work was to produce a blueprint for the synthesis and characterisation of non-pyrogenic graphene oxide (GO) flakes with three different controlled lateral dimensions, which could be further used for either hazard assessment or biomedical proof-of-concept studies. A battery of techniques used to characterise the physicochemical properties of the GO samples included atomic force microscopy, transmission electron microscopy, Fourier-transformed infra-red spectroscopy, x-ray photoelectron spectroscopy and Raman spectroscopy. The combination of these different techniques confirmed that only the lateral dimension varied among the GO materials produced, without significant change in any other of their fundamental physicochemical properties, such as the thickness or surface chemistry. The proposed systematic approach in GO batch production for biology will hopefully contribute to a better understanding of the material properties that govern their interactions with biological systems and offer a blueprint towards standardisation of biologically relevant 2D materials.

Do Zoo Visitors Need Zoology Knowledge to Understand Conservation Messages? An Exploration of the Public Understanding of Animal Biology and of the Conservation of Biodiversity in a Zoo Setting

ERIC Educational Resources Information Center

Dove, Tracy; Byrne, Jenny

2014-01-01

This study explores the current knowledge and understanding about animal biology of zoo visitors and investigates whether knowledge of animal biology influences the ability of people to understand how human activity affects biodiversity. Zoos can play a role in the development of scientific literacy in the fields of animal biology and biodiversity…

Processing Of Visual Information In Primate Brains

NASA Technical Reports Server (NTRS)

Anderson, Charles H.; Van Essen, David C.

1991-01-01

Report reviews and analyzes information-processing strategies and pathways in primate retina and visual cortex. Of interest both in biological fields and in such related computational fields as artificial neural networks. Focuses on data from macaque, which has superb visual system similar to that of humans. Authors stress concept of "good engineering" in understanding visual system.

Cellular respiration: replicating in vivo systems biology for in vitro exploration of human exposome, microbiome, and disease pathogenesis biomarkers

EPA Science Inventory

This editorial develops a philosophy for expanding the scope of Journal of Breath Research (JBR) into the realm of cellular level study, and links certain topics back to more traditional systemic research for understanding human health based on exhaled breath constituents. The ex...

Student-Designed Enzyme-Linked Metabolite Assay Kits

ERIC Educational Resources Information Center

Hancock, D.; Johnston, J.; Dimauro, J.; Denyer, G.

2004-01-01

The extensive use of commercial kits in molecular biology and biochemistry has prompted us to design a series of practical sessions to help students become familiar with the uses and limitations of pre-packaged assay systems. To facilitate an understanding of these assay systems and to promote reflection on their appropriate use, students…

Novel approach using DNA-RNA hybrids in RNA nanotechnology | Center for Cancer Research

Cancer.gov

Developing simple approaches to detect interactions, modifications, and cellular locations of macromolecules is essential for understanding biochemical processes. The use of protein fragment complementation assays, also called split-protein systems, is a highly sensitive approach for studying protein interactions in biological systems. In this approach, functional proteins are

Synthetic biology approaches in drug discovery and pharmaceutical biotechnology.

PubMed

Neumann, Heinz; Neumann-Staubitz, Petra

2010-06-01

Synthetic biology is the attempt to apply the concepts of engineering to biological systems with the aim to create organisms with new emergent properties. These organisms might have desirable novel biosynthetic capabilities, act as biosensors or help us to understand the intricacies of living systems. This approach has the potential to assist the discovery and production of pharmaceutical compounds at various stages. New sources of bioactive compounds can be created in the form of genetically encoded small molecule libraries. The recombination of individual parts has been employed to design proteins that act as biosensors, which could be used to identify and quantify molecules of interest. New biosynthetic pathways may be designed by stitching together enzymes with desired activities, and genetic code expansion can be used to introduce new functionalities into peptides and proteins to increase their chemical scope and biological stability. This review aims to give an insight into recently developed individual components and modules that might serve as parts in a synthetic biology approach to pharmaceutical biotechnology.

Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity

PubMed Central

Liang, Jie; Qian, Hong

2010-01-01

Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand “complex behavior” and complexity theory, and from which important biological insight can be gained. PMID:24999297

Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity.

PubMed

Liang, Jie; Qian, Hong

2010-01-01

Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand "complex behavior" and complexity theory, and from which important biological insight can be gained.

Spontaneous ultraweak photon emission from biological systems and the endogenous light field.

PubMed

Schwabl, Herbert; Klima, Herbert

2005-04-01

Still one of the most astonishing biological electromagnetic phenomena is the ultraweak photon emission (UPE) from living systems. Organisms and tissues spontaneously emit measurable intensities of light, i.e. photons in the visible part of the electromagnetic spectrum (380-780 nm), in the range from 1 to 1,000 photons x s-1 x cm-2, depending on their condition and vitality. It is important not to confuse UPE from living systems with other biogenic light emitting processes such as bioluminescence or chemiluminescence. This article examines with basic considerations from physics on the quantum nature of photons the empirical phenomenon of UPE. This leads to the description of the non-thermal origin of this radiation. This is in good correspondence with the modern understanding of life phenomena as dissipative processes far from thermodynamic equilibrium. UPE also supports the understanding of life sustaining processes as basically driven by electromagnetic fields. The basic features of UPE, like intensity and spectral distribution, are known in principle for many experimental situations. The UPE of human leukocytes contributes to an endogenous light field of about 1011 photons x s-1 which can be influenced by certain factors. Further research is needed to reveal the statistical properties of UPE and in consequence to answer questions about the underlying mechanics of the biological system. In principle, statistical properties of UPE allow to reconstruct phase-space dynamics of the light emitting structures. Many open questions remain until a proper understanding of the electromagnetic interaction of the human organism can be achieved: which structures act as receptors and emitters for electromagnetic radiation? How is electromagnetic information received and processed within cells?

CHEMICAL PROCESSES AND MODELING IN ECOSYSTEMS

EPA Science Inventory

Trends in regulatory strategies require EPA to understand better chemical behavior in natural and impacted ecosystems and in biological systems to carry out the increasingly complex array of exposure and risk assessments needed to develop scientifically defensible regulations (GP...

A reverse engineering approach to optimize experiments for the construction of biological regulatory networks.

PubMed

Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang

2013-01-01

One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.